testing_unified_ensemble_non_ensemble_models.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import grequests\n",
    "import src.Engines.gdc_engine as gdc_engine\n",
    "import src.MLPreprocessor.RNASeqPreprocessor as rna_pp\n",
    "import src.Connectors.gcp_bigquery_utils as gcp_bigquery_utils"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 0. Process the data\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n",
      "I0000 00:00:1725950047.917240 3576609 config.cc:230] gRPC experiments enabled: call_status_override_on_cancellation, event_engine_dns, event_engine_listener, http2_stats_fix, monitoring_experiment, pick_first_new, trace_record_callops, work_serializer_clears_time_cache\n",
      "I0000 00:00:1725950047.930252 3576609 check_gcp_environment_no_op.cc:29] ALTS: Platforms other than Linux and Windows are not supported\n",
      "I0000 00:00:1725950057.686395 3576609 check_gcp_environment_no_op.cc:29] ALTS: Platforms other than Linux and Windows are not supported\n"
     ]
    }
   ],
   "source": [
    "project_id = 'rnaseqml'\n",
    "dataset_id = 'rnaseqexpression'\n",
    "table_id = 'expr_clustered_08082024'\n",
    "bq_queries = gcp_bigquery_utils.BigQueryQueries(project_id=project_id, \n",
    "                                              dataset_id=dataset_id,\n",
    "                                              table_id=table_id)\n",
    "pr_site = 'Head and Neck'\n",
    "pr_diag = 'Squamous cell carcinoma, NOS'\n",
    "data_from_bq = bq_queries.get_df_for_pydeseq(primary_site=pr_site, primary_diagnosis=pr_diag)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dict_keys(['files.experimental_strategy', 'data_type'])\n",
      "file_id,file_name,submitter_id,experimental_strategy,data_type,platform,cases.case_id,cases.project.name,cases.project.project_id,cases.project.program.name,cases.project.program.program_id,cases.samples.sample_id,cases.diagnoses.last_known_disease_status,cases.diagnoses.primary_diagnosis,cases.diagnoses.tumor_stage,cases.diagnoses.tumor_grade,cases.diagnoses.treatments.treatment_or_therapy,cases.diagnoses.days_to_last_follow_up,cases.diagnoses.age_at_diagnosis,cases.diagnoses.days_to_death,cases.project.primary_site,analysis.workflow_type,cases.demographic.ethnicity,cases.demographic.gender,cases.demographic.race,cases.diagnoses.tissue_or_organ_of_origin,cases.exposures.bmi,cases.exposures.alcohol_history,cases.exposures.years_smoked,cases.samples.tissue_type,cases.samples.sample_typecases.samples.is_ffpe,cases.samples.preservation_method,cases.diagnoses.tumor_stage,cases.diagnoses.tumor_grade,cases.diagnoses.age_at_diagnosis,cases.demographic.gender,cases.demographic.race,cases.demographic.ethnicity,cases.exposures.alcohol_history,cases.exposures.cigarettes_per_day,cases.exposures.years_smoked,cases.project.disease_type,experimental_strategy,analysis.workflow_type,files.cases.follow_ups.days_to_progression_free\n",
      "dict_keys(['files.experimental_strategy', 'data_type'])\n",
      "file_id,file_name,submitter_id,experimental_strategy,data_type,platform,cases.case_id,cases.project.name,cases.project.project_id,cases.project.program.name,cases.project.program.program_id,cases.samples.sample_id,cases.diagnoses.last_known_disease_status,cases.diagnoses.primary_diagnosis,cases.diagnoses.tumor_stage,cases.diagnoses.tumor_grade,cases.diagnoses.treatments.treatment_or_therapy,cases.diagnoses.days_to_last_follow_up,cases.diagnoses.age_at_diagnosis,cases.diagnoses.days_to_death,cases.project.primary_site,analysis.workflow_type,cases.demographic.ethnicity,cases.demographic.gender,cases.demographic.race,cases.diagnoses.tissue_or_organ_of_origin,cases.exposures.bmi,cases.exposures.alcohol_history,cases.exposures.years_smoked,cases.samples.tissue_type,cases.samples.sample_typecases.samples.is_ffpe,cases.samples.preservation_method,cases.diagnoses.tumor_stage,cases.diagnoses.tumor_grade,cases.diagnoses.age_at_diagnosis,cases.demographic.gender,cases.demographic.race,cases.demographic.ethnicity,cases.exposures.alcohol_history,cases.exposures.cigarettes_per_day,cases.exposures.years_smoked,cases.project.disease_type,experimental_strategy,analysis.workflow_type,files.cases.follow_ups.days_to_progression_free\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 50/50 [00:00<00:00, 74.06it/s]\n",
      "100%|██████████| 50/50 [00:00<00:00, 75.36it/s]\n",
      "100%|██████████| 50/50 [00:02<00:00, 16.87it/s]\n",
      "100%|██████████| 50/50 [00:01<00:00, 46.63it/s]\n",
      "100%|██████████| 50/50 [00:00<00:00, 60.50it/s]\n",
      "100%|██████████| 50/50 [00:00<00:00, 80.19it/s]\n",
      "100%|██████████| 50/50 [00:00<00:00, 77.78it/s]\n",
      "100%|██████████| 50/50 [00:00<00:00, 72.34it/s]\n",
      "100%|██████████| 50/50 [00:00<00:00, 84.08it/s]\n",
      "100%|██████████| 50/50 [00:00<00:00, 81.58it/s]\n",
      "100%|██████████| 50/50 [00:00<00:00, 84.44it/s]\n",
      "100%|██████████| 11/11 [07:56<00:00, 43.31s/it]\n"
     ]
    }
   ],
   "source": [
    "params = {\n",
    "    'files.experimental_strategy': 'RNA-Seq', \n",
    "    'data_type': 'Gene Expression Quantification'\n",
    "}\n",
    "site = 'Head and Neck'\n",
    "gdc_eng_inst = gdc_engine.GDCEngine(**params)\n",
    "json_object, gene_cols = gdc_eng_inst.make_count_data_for_bq(site, downstream_analysis='DE', format='json')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/200\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 2s/step - loss: 0.9066 - val_loss: 0.6541 - learning_rate: 0.0010\n",
      "Epoch 2/200\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 645ms/step - loss: 0.9063 - val_loss: 0.6586 - learning_rate: 0.0010\n",
      "Epoch 3/200\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 253ms/step - loss: 0.8966 - val_loss: 0.6641 - learning_rate: 0.0010\n",
      "Epoch 4/200\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 203ms/step - loss: 0.8359 - val_loss: 0.6628 - learning_rate: 0.0010\n",
      "Epoch 5/200\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 294ms/step - loss: 0.7991 - val_loss: 0.6648 - learning_rate: 0.0010\n",
      "Epoch 6/200\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 423ms/step - loss: 0.8275 - val_loss: 0.6614 - learning_rate: 0.0010\n",
      "Epoch 7/200\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 381ms/step - loss: 0.7970 - val_loss: 0.6617 - learning_rate: 2.0000e-04\n",
      "Epoch 8/200\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 362ms/step - loss: 0.7929 - val_loss: 0.6620 - learning_rate: 2.0000e-04\n",
      "Epoch 9/200\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 319ms/step - loss: 0.7812 - val_loss: 0.6624 - learning_rate: 2.0000e-04\n",
      "Epoch 10/200\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 263ms/step - loss: 0.7672 - val_loss: 0.6630 - learning_rate: 2.0000e-04\n",
      "Epoch 11/200\n",
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 205ms/step - loss: 0.7550 - val_loss: 0.6638 - learning_rate: 2.0000e-04\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 14ms/step\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 12ms/step\n"
     ]
    }
   ],
   "source": [
    "preprocessor = rna_pp.RNASeqPP(data_from_bq, gene_cols)\n",
    "X_train, X_test, X_val, y_train, y_test, y_val = preprocessor.prepare_data()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ENSG00000000003.15</th>\n",
       "      <th>ENSG00000000005.6</th>\n",
       "      <th>ENSG00000000419.13</th>\n",
       "      <th>ENSG00000000457.14</th>\n",
       "      <th>ENSG00000000460.17</th>\n",
       "      <th>ENSG00000000938.13</th>\n",
       "      <th>ENSG00000000971.16</th>\n",
       "      <th>ENSG00000001036.14</th>\n",
       "      <th>ENSG00000001084.13</th>\n",
       "      <th>ENSG00000001167.14</th>\n",
       "      <th>...</th>\n",
       "      <th>ENSG00000288661.1</th>\n",
       "      <th>ENSG00000288662.1</th>\n",
       "      <th>ENSG00000288663.1</th>\n",
       "      <th>ENSG00000288665.1</th>\n",
       "      <th>ENSG00000288667.1</th>\n",
       "      <th>ENSG00000288669.1</th>\n",
       "      <th>ENSG00000288670.1</th>\n",
       "      <th>ENSG00000288671.1</th>\n",
       "      <th>ENSG00000288674.1</th>\n",
       "      <th>ENSG00000288675.1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7.170120</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.980076</td>\n",
       "      <td>5.802118</td>\n",
       "      <td>5.886104</td>\n",
       "      <td>5.616771</td>\n",
       "      <td>8.047829</td>\n",
       "      <td>7.640123</td>\n",
       "      <td>6.963190</td>\n",
       "      <td>6.896694</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.397895</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.236442</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.806662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7.275172</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.768956</td>\n",
       "      <td>5.620401</td>\n",
       "      <td>5.509388</td>\n",
       "      <td>4.934474</td>\n",
       "      <td>7.427144</td>\n",
       "      <td>7.225481</td>\n",
       "      <td>8.162516</td>\n",
       "      <td>6.834109</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.386294</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.693147</td>\n",
       "      <td>4.521789</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.397895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7.632401</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.100852</td>\n",
       "      <td>6.317165</td>\n",
       "      <td>6.030685</td>\n",
       "      <td>6.573680</td>\n",
       "      <td>7.753194</td>\n",
       "      <td>7.330405</td>\n",
       "      <td>9.931686</td>\n",
       "      <td>7.315884</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.693147</td>\n",
       "      <td>3.178054</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.605170</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.386294</td>\n",
       "      <td>2.833213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6.664409</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.760041</td>\n",
       "      <td>5.789960</td>\n",
       "      <td>5.793014</td>\n",
       "      <td>5.068904</td>\n",
       "      <td>7.215240</td>\n",
       "      <td>7.369601</td>\n",
       "      <td>6.677083</td>\n",
       "      <td>7.076654</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.693147</td>\n",
       "      <td>3.555348</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.709530</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>1.945910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8.193400</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.952615</td>\n",
       "      <td>5.730100</td>\n",
       "      <td>5.866468</td>\n",
       "      <td>4.912655</td>\n",
       "      <td>6.401917</td>\n",
       "      <td>7.638680</td>\n",
       "      <td>9.626350</td>\n",
       "      <td>7.077498</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.693147</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.323010</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>2.564949</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>489</th>\n",
       "      <td>7.630947</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.710653</td>\n",
       "      <td>6.429719</td>\n",
       "      <td>6.418365</td>\n",
       "      <td>6.182085</td>\n",
       "      <td>8.167636</td>\n",
       "      <td>7.533694</td>\n",
       "      <td>8.458504</td>\n",
       "      <td>7.559559</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.890372</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.327876</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>3.044522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>490</th>\n",
       "      <td>7.626083</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.719574</td>\n",
       "      <td>6.423247</td>\n",
       "      <td>6.391917</td>\n",
       "      <td>6.182085</td>\n",
       "      <td>8.170469</td>\n",
       "      <td>7.530480</td>\n",
       "      <td>8.456381</td>\n",
       "      <td>7.560601</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.890372</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.327876</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>3.044522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>491</th>\n",
       "      <td>7.617268</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.726654</td>\n",
       "      <td>6.416732</td>\n",
       "      <td>6.400257</td>\n",
       "      <td>6.171701</td>\n",
       "      <td>8.171034</td>\n",
       "      <td>7.530480</td>\n",
       "      <td>8.460834</td>\n",
       "      <td>7.563201</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.890372</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.332719</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>3.044522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>492</th>\n",
       "      <td>7.624131</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.714231</td>\n",
       "      <td>6.424869</td>\n",
       "      <td>6.405228</td>\n",
       "      <td>6.173786</td>\n",
       "      <td>8.165932</td>\n",
       "      <td>7.531552</td>\n",
       "      <td>8.457018</td>\n",
       "      <td>7.558517</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.890372</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.337538</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>3.044522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>493</th>\n",
       "      <td>7.642524</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.709757</td>\n",
       "      <td>6.440947</td>\n",
       "      <td>6.403574</td>\n",
       "      <td>6.171701</td>\n",
       "      <td>8.162801</td>\n",
       "      <td>7.532088</td>\n",
       "      <td>8.457231</td>\n",
       "      <td>7.552762</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.833213</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.327876</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>3.044522</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>494 rows × 60660 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     ENSG00000000003.15  ENSG00000000005.6  ENSG00000000419.13  \\\n",
       "0              7.170120                0.0            6.980076   \n",
       "1              7.275172                0.0            7.768956   \n",
       "2              7.632401                0.0            7.100852   \n",
       "3              6.664409                0.0            7.760041   \n",
       "4              8.193400                0.0            7.952615   \n",
       "..                  ...                ...                 ...   \n",
       "489            7.630947                0.0            7.710653   \n",
       "490            7.626083                0.0            7.719574   \n",
       "491            7.617268                0.0            7.726654   \n",
       "492            7.624131                0.0            7.714231   \n",
       "493            7.642524                0.0            7.709757   \n",
       "\n",
       "     ENSG00000000457.14  ENSG00000000460.17  ENSG00000000938.13  \\\n",
       "0              5.802118            5.886104            5.616771   \n",
       "1              5.620401            5.509388            4.934474   \n",
       "2              6.317165            6.030685            6.573680   \n",
       "3              5.789960            5.793014            5.068904   \n",
       "4              5.730100            5.866468            4.912655   \n",
       "..                  ...                 ...                 ...   \n",
       "489            6.429719            6.418365            6.182085   \n",
       "490            6.423247            6.391917            6.182085   \n",
       "491            6.416732            6.400257            6.171701   \n",
       "492            6.424869            6.405228            6.173786   \n",
       "493            6.440947            6.403574            6.171701   \n",
       "\n",
       "     ENSG00000000971.16  ENSG00000001036.14  ENSG00000001084.13  \\\n",
       "0              8.047829            7.640123            6.963190   \n",
       "1              7.427144            7.225481            8.162516   \n",
       "2              7.753194            7.330405            9.931686   \n",
       "3              7.215240            7.369601            6.677083   \n",
       "4              6.401917            7.638680            9.626350   \n",
       "..                  ...                 ...                 ...   \n",
       "489            8.167636            7.533694            8.458504   \n",
       "490            8.170469            7.530480            8.456381   \n",
       "491            8.171034            7.530480            8.460834   \n",
       "492            8.165932            7.531552            8.457018   \n",
       "493            8.162801            7.532088            8.457231   \n",
       "\n",
       "     ENSG00000001167.14  ...  ENSG00000288661.1  ENSG00000288662.1  \\\n",
       "0              6.896694  ...                0.0           0.000000   \n",
       "1              6.834109  ...                0.0           0.000000   \n",
       "2              7.315884  ...                0.0           0.693147   \n",
       "3              7.076654  ...                0.0           0.693147   \n",
       "4              7.077498  ...                0.0           0.000000   \n",
       "..                  ...  ...                ...                ...   \n",
       "489            7.559559  ...                0.0           0.000000   \n",
       "490            7.560601  ...                0.0           0.000000   \n",
       "491            7.563201  ...                0.0           0.000000   \n",
       "492            7.558517  ...                0.0           0.000000   \n",
       "493            7.552762  ...                0.0           0.000000   \n",
       "\n",
       "     ENSG00000288663.1  ENSG00000288665.1  ENSG00000288667.1  \\\n",
       "0             2.397895                0.0                0.0   \n",
       "1             1.386294                0.0                0.0   \n",
       "2             3.178054                0.0                0.0   \n",
       "3             3.555348                0.0                0.0   \n",
       "4             0.693147                0.0                0.0   \n",
       "..                 ...                ...                ...   \n",
       "489           2.890372                0.0                0.0   \n",
       "490           2.890372                0.0                0.0   \n",
       "491           2.890372                0.0                0.0   \n",
       "492           2.890372                0.0                0.0   \n",
       "493           2.833213                0.0                0.0   \n",
       "\n",
       "     ENSG00000288669.1  ENSG00000288670.1  ENSG00000288671.1  \\\n",
       "0             0.000000           5.236442                0.0   \n",
       "1             0.693147           4.521789                0.0   \n",
       "2             0.000000           4.605170                0.0   \n",
       "3             0.000000           4.709530                0.0   \n",
       "4             0.000000           5.323010                0.0   \n",
       "..                 ...                ...                ...   \n",
       "489           0.000000           5.327876                0.0   \n",
       "490           0.000000           5.327876                0.0   \n",
       "491           0.000000           5.332719                0.0   \n",
       "492           0.000000           5.337538                0.0   \n",
       "493           0.000000           5.327876                0.0   \n",
       "\n",
       "     ENSG00000288674.1  ENSG00000288675.1  \n",
       "0             0.000000           3.806662  \n",
       "1             0.000000           2.397895  \n",
       "2             1.386294           2.833213  \n",
       "3             1.098612           1.945910  \n",
       "4             1.098612           2.564949  \n",
       "..                 ...                ...  \n",
       "489           1.098612           3.044522  \n",
       "490           1.098612           3.044522  \n",
       "491           1.098612           3.044522  \n",
       "492           1.098612           3.044522  \n",
       "493           1.098612           3.044522  \n",
       "\n",
       "[494 rows x 60660 columns]"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##  Classification Experiments\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.9615\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.9615\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/neural_network/_multilayer_perceptron.py:691: ConvergenceWarning:\n",
      "\n",
      "Stochastic Optimizer: Maximum iterations (200) reached and the optimization hasn't converged yet.\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.9551\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.9872\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "from sklearn.datasets import make_classification\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.neural_network import MLPClassifier\n",
    "# from src.ClassicML.Supervised.base_models import SVMModel, RandomForestModel, NeuralNetworkModel, EnsembleModel\n",
    "import src.ClassicML.Supervised.base_models as base_models\n",
    "import src.ClassicML.DimRedMappers.feature_explainer as fe\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "from importlib import reload\n",
    "reload(base_models)\n",
    "reload(fe)\n",
    "\n",
    "\n",
    "# Run non-ensemble models\n",
    "svm_model, y_pred_svm, accuracy_svm = base_models.SVMModel(n_components=10).run_model(X_train, X_test, y_train, y_test, reduce_dim=True, method='PCA')\n",
    "rf_model, y_pred_rf, accuracy_rf  = base_models.RandomForestModel(n_components=5).run_model(X_train, X_test, y_train, y_test, reduce_dim=True, method='PCA')\n",
    "nn_model, y_pred_nn, accuracy_nn  = base_models.NeuralNetworkModel(n_components=5).run_model(X_train, X_test, y_train, y_test, reduce_dim=True, method='PCA')\n",
    "\n",
    "# Run ensemble model\n",
    "base_estimators = [\n",
    "    SVC(probability=True, random_state=42),\n",
    "    RandomForestClassifier(random_state=42),\n",
    "    MLPClassifier(random_state=42)\n",
    "]\n",
    "ensemble_model = base_models.EnsembleModel(base_estimators=base_estimators)\n",
    "ensemble_model_run, y_pred_ensemble, accuracy_ensemble = ensemble_model.run_model(X_train, X_test, y_train, y_test, reduce_dim=True, method='PCA')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Running the LRA "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but PCA was fitted without feature names\n",
      "\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "07d3589498a44882a75865c7cb39715a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/156 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "# Usage example\n",
    "lra = fe.LRA(model=svm_model)\n",
    "\n",
    "# Run LRA for a single method\n",
    "method = 'PCA'\n",
    "shap_results = lra.run_single_method(X_train, y_train, X_test, y_test, method)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                  feature    lra_metric  abs_lra_metric\n",
      "30595   ENSG00000232150.3 -1.829397e-10    1.829397e-10\n",
      "7104   ENSG00000135537.17 -1.828920e-10    1.828920e-10\n",
      "15062  ENSG00000181588.16 -1.828210e-10    1.828210e-10\n",
      "5078    ENSG00000120688.9 -1.827516e-10    1.827516e-10\n",
      "4117   ENSG00000112855.17 -1.827074e-10    1.827074e-10\n",
      "5677   ENSG00000125629.15 -1.826550e-10    1.826550e-10\n",
      "5108   ENSG00000120889.13 -1.826085e-10    1.826085e-10\n",
      "8895   ENSG00000146872.18 -1.825863e-10    1.825863e-10\n",
      "4830   ENSG00000118600.12 -1.825686e-10    1.825686e-10\n",
      "10219  ENSG00000158480.11 -1.825398e-10    1.825398e-10\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Load gene name to gene id mapping\n",
    "gene_name_to_gene_id = pd.read_csv('/Users/abhilashdhal/Projects/personal_docs/data/Transcriptomics/data/gene_annotation/gene_id_to_gene_name_mapping.csv')\n",
    "\n",
    "# Calculate LRA metric\n",
    "shap_values = shap_results['PCA']\n",
    "\n",
    "# Check if dimensionality reduction was applied\n",
    "if len(shap_values) == X_test.shape[1]:\n",
    "    # No dimensionality reduction\n",
    "    feature_names = [gene_cols[i] for i in range(X_test.shape[1])]\n",
    "else:\n",
    "    # Dimensionality reduction was applied\n",
    "    feature_names = [f'PC_{i+1}' for i in range(len(shap_values))]\n",
    "\n",
    "lra_df = pd.DataFrame({\n",
    "    'feature': feature_names,\n",
    "    'lra_metric': shap_values\n",
    "})\n",
    "\n",
    "lra_df['abs_lra_metric'] = np.abs(lra_df['lra_metric'])\n",
    "\n",
    "# Sort the dataframe\n",
    "lra_df_sorted = lra_df.sort_values('abs_lra_metric', ascending=False)\n",
    "\n",
    "print(lra_df_sorted.head(10))\n",
    "\n",
    "# Visualization\n",
    "plt.figure(figsize=(10, 6))\n",
    "sns.barplot(x='lra_metric', y='feature', data=lra_df_sorted.head(50))\n",
    "plt.title(f'Top 50 Features by LRA Metric ({method.upper()})')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ENSG00000000003.15</th>\n",
       "      <th>ENSG00000000005.6</th>\n",
       "      <th>ENSG00000000419.13</th>\n",
       "      <th>ENSG00000000457.14</th>\n",
       "      <th>ENSG00000000460.17</th>\n",
       "      <th>ENSG00000000938.13</th>\n",
       "      <th>ENSG00000000971.16</th>\n",
       "      <th>ENSG00000001036.14</th>\n",
       "      <th>ENSG00000001084.13</th>\n",
       "      <th>ENSG00000001167.14</th>\n",
       "      <th>...</th>\n",
       "      <th>ENSG00000288661.1</th>\n",
       "      <th>ENSG00000288662.1</th>\n",
       "      <th>ENSG00000288663.1</th>\n",
       "      <th>ENSG00000288665.1</th>\n",
       "      <th>ENSG00000288667.1</th>\n",
       "      <th>ENSG00000288669.1</th>\n",
       "      <th>ENSG00000288670.1</th>\n",
       "      <th>ENSG00000288671.1</th>\n",
       "      <th>ENSG00000288674.1</th>\n",
       "      <th>ENSG00000288675.1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6.809039</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.030857</td>\n",
       "      <td>6.163315</td>\n",
       "      <td>5.746203</td>\n",
       "      <td>4.867534</td>\n",
       "      <td>7.358831</td>\n",
       "      <td>6.715383</td>\n",
       "      <td>8.375399</td>\n",
       "      <td>7.012115</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.302585</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.129899</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.833213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7.386471</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.774436</td>\n",
       "      <td>6.489205</td>\n",
       "      <td>5.703782</td>\n",
       "      <td>5.549076</td>\n",
       "      <td>7.800163</td>\n",
       "      <td>7.201916</td>\n",
       "      <td>7.253470</td>\n",
       "      <td>7.436028</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.091042</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.990433</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>3.135494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7.760041</td>\n",
       "      <td>0.693147</td>\n",
       "      <td>7.813592</td>\n",
       "      <td>6.291569</td>\n",
       "      <td>6.390241</td>\n",
       "      <td>6.196444</td>\n",
       "      <td>7.918992</td>\n",
       "      <td>7.652071</td>\n",
       "      <td>9.025816</td>\n",
       "      <td>7.429521</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.218876</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.693147</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.897154</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>2.944439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8.040769</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.636270</td>\n",
       "      <td>6.689599</td>\n",
       "      <td>7.011214</td>\n",
       "      <td>5.068904</td>\n",
       "      <td>8.778942</td>\n",
       "      <td>8.315811</td>\n",
       "      <td>7.985484</td>\n",
       "      <td>7.304516</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.258097</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.609438</td>\n",
       "      <td>5.620401</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.386294</td>\n",
       "      <td>2.079442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7.358194</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>8.111328</td>\n",
       "      <td>6.647688</td>\n",
       "      <td>6.297109</td>\n",
       "      <td>5.648974</td>\n",
       "      <td>7.579168</td>\n",
       "      <td>7.612831</td>\n",
       "      <td>10.313973</td>\n",
       "      <td>8.192847</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.944439</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.860786</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>2.833213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>8.490028</td>\n",
       "      <td>3.465736</td>\n",
       "      <td>7.412764</td>\n",
       "      <td>6.815640</td>\n",
       "      <td>5.793014</td>\n",
       "      <td>6.089045</td>\n",
       "      <td>8.985570</td>\n",
       "      <td>7.371489</td>\n",
       "      <td>8.099858</td>\n",
       "      <td>7.186144</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.945910</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.303305</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.609438</td>\n",
       "      <td>2.995732</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>7.630461</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.719130</td>\n",
       "      <td>6.418365</td>\n",
       "      <td>6.405228</td>\n",
       "      <td>6.180017</td>\n",
       "      <td>8.171317</td>\n",
       "      <td>7.533694</td>\n",
       "      <td>8.457655</td>\n",
       "      <td>7.559559</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.833213</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.332719</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>3.044522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>7.628518</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.717796</td>\n",
       "      <td>6.419995</td>\n",
       "      <td>6.408529</td>\n",
       "      <td>6.188264</td>\n",
       "      <td>8.160804</td>\n",
       "      <td>7.526718</td>\n",
       "      <td>8.446985</td>\n",
       "      <td>7.564757</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.833213</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.327876</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>3.044522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>7.629976</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.715124</td>\n",
       "      <td>6.429719</td>\n",
       "      <td>6.390241</td>\n",
       "      <td>6.175867</td>\n",
       "      <td>8.167919</td>\n",
       "      <td>7.531552</td>\n",
       "      <td>8.450840</td>\n",
       "      <td>7.561642</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.890372</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.318120</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>3.044522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>7.624131</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.724005</td>\n",
       "      <td>6.423247</td>\n",
       "      <td>6.406880</td>\n",
       "      <td>6.167516</td>\n",
       "      <td>8.165079</td>\n",
       "      <td>7.529943</td>\n",
       "      <td>8.455105</td>\n",
       "      <td>7.561642</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.890372</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.332719</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>3.044522</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>156 rows × 60660 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     ENSG00000000003.15  ENSG00000000005.6  ENSG00000000419.13  \\\n",
       "0              6.809039           0.000000            7.030857   \n",
       "1              7.386471           0.000000            7.774436   \n",
       "2              7.760041           0.693147            7.813592   \n",
       "3              8.040769           0.000000            7.636270   \n",
       "4              7.358194           0.000000            8.111328   \n",
       "..                  ...                ...                 ...   \n",
       "151            8.490028           3.465736            7.412764   \n",
       "152            7.630461           0.000000            7.719130   \n",
       "153            7.628518           0.000000            7.717796   \n",
       "154            7.629976           0.000000            7.715124   \n",
       "155            7.624131           0.000000            7.724005   \n",
       "\n",
       "     ENSG00000000457.14  ENSG00000000460.17  ENSG00000000938.13  \\\n",
       "0              6.163315            5.746203            4.867534   \n",
       "1              6.489205            5.703782            5.549076   \n",
       "2              6.291569            6.390241            6.196444   \n",
       "3              6.689599            7.011214            5.068904   \n",
       "4              6.647688            6.297109            5.648974   \n",
       "..                  ...                 ...                 ...   \n",
       "151            6.815640            5.793014            6.089045   \n",
       "152            6.418365            6.405228            6.180017   \n",
       "153            6.419995            6.408529            6.188264   \n",
       "154            6.429719            6.390241            6.175867   \n",
       "155            6.423247            6.406880            6.167516   \n",
       "\n",
       "     ENSG00000000971.16  ENSG00000001036.14  ENSG00000001084.13  \\\n",
       "0              7.358831            6.715383            8.375399   \n",
       "1              7.800163            7.201916            7.253470   \n",
       "2              7.918992            7.652071            9.025816   \n",
       "3              8.778942            8.315811            7.985484   \n",
       "4              7.579168            7.612831           10.313973   \n",
       "..                  ...                 ...                 ...   \n",
       "151            8.985570            7.371489            8.099858   \n",
       "152            8.171317            7.533694            8.457655   \n",
       "153            8.160804            7.526718            8.446985   \n",
       "154            8.167919            7.531552            8.450840   \n",
       "155            8.165079            7.529943            8.455105   \n",
       "\n",
       "     ENSG00000001167.14  ...  ENSG00000288661.1  ENSG00000288662.1  \\\n",
       "0              7.012115  ...                0.0                0.0   \n",
       "1              7.436028  ...                0.0                0.0   \n",
       "2              7.429521  ...                0.0                0.0   \n",
       "3              7.304516  ...                0.0                0.0   \n",
       "4              8.192847  ...                0.0                0.0   \n",
       "..                  ...  ...                ...                ...   \n",
       "151            7.186144  ...                0.0                0.0   \n",
       "152            7.559559  ...                0.0                0.0   \n",
       "153            7.564757  ...                0.0                0.0   \n",
       "154            7.561642  ...                0.0                0.0   \n",
       "155            7.561642  ...                0.0                0.0   \n",
       "\n",
       "     ENSG00000288663.1  ENSG00000288665.1  ENSG00000288667.1  \\\n",
       "0             2.302585                0.0           0.000000   \n",
       "1             3.091042                0.0           0.000000   \n",
       "2             3.218876                0.0           0.693147   \n",
       "3             3.258097                0.0           0.000000   \n",
       "4             2.944439                0.0           0.000000   \n",
       "..                 ...                ...                ...   \n",
       "151           1.945910                0.0           0.000000   \n",
       "152           2.833213                0.0           0.000000   \n",
       "153           2.833213                0.0           0.000000   \n",
       "154           2.890372                0.0           0.000000   \n",
       "155           2.890372                0.0           0.000000   \n",
       "\n",
       "     ENSG00000288669.1  ENSG00000288670.1  ENSG00000288671.1  \\\n",
       "0             0.000000           5.129899                0.0   \n",
       "1             0.000000           4.990433                0.0   \n",
       "2             0.000000           5.897154                0.0   \n",
       "3             1.609438           5.620401                0.0   \n",
       "4             0.000000           5.860786                0.0   \n",
       "..                 ...                ...                ...   \n",
       "151           0.000000           5.303305                0.0   \n",
       "152           0.000000           5.332719                0.0   \n",
       "153           0.000000           5.327876                0.0   \n",
       "154           0.000000           5.318120                0.0   \n",
       "155           0.000000           5.332719                0.0   \n",
       "\n",
       "     ENSG00000288674.1  ENSG00000288675.1  \n",
       "0             0.000000           2.833213  \n",
       "1             1.098612           3.135494  \n",
       "2             1.098612           2.944439  \n",
       "3             1.386294           2.079442  \n",
       "4             1.098612           2.833213  \n",
       "..                 ...                ...  \n",
       "151           1.609438           2.995732  \n",
       "152           1.098612           3.044522  \n",
       "153           1.098612           3.044522  \n",
       "154           1.098612           3.044522  \n",
       "155           1.098612           3.044522  \n",
       "\n",
       "[156 rows x 60660 columns]"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_test"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Explainatory Analysis\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Using dalex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Preparation of a new explainer is initiated\n",
      "\n",
      "  -> data              : numpy.ndarray converted to pandas.DataFrame. Columns are set as string numbers.\n",
      "  -> data              : 156 rows 5 cols\n",
      "  -> target variable   : 156 values\n",
      "  -> model_class       : src.ClassicML.Supervised.base_models.SVMModel (default)\n",
      "  -> label             : Not specified, model's class short name will be used. (default)\n",
      "  -> predict function  : <function yhat_proba_default at 0x3a2dfae80> will be used (default)\n",
      "  -> predict function  : Accepts pandas.DataFrame and numpy.ndarray.\n",
      "  -> predicted values  : min = 0.0159, mean = 0.752, max = 0.97\n",
      "  -> model type        : classification will be used (default)\n",
      "  -> residual function : difference between y and yhat (default)\n",
      "  -> residuals         : min = -0.925, mean = -0.252, max = 0.984\n",
      "  -> model_info        : package src\n",
      "\n",
      "A new explainer has been created!\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import dalex as dx\n",
    "exp = dx.Explainer(svm_model, svm_model._fit_transform(X_test, method='pca'), y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>recall</th>\n",
       "      <th>precision</th>\n",
       "      <th>f1</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>auc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>SVMModel</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.987342</td>\n",
       "      <td>0.993631</td>\n",
       "      <td>0.99359</td>\n",
       "      <td>0.998521</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          recall  precision        f1  accuracy       auc\n",
       "SVMModel     1.0   0.987342  0.993631   0.99359  0.998521"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "exp.model_performance().result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n",
      "/opt/homebrew/anaconda3/envs/omixhub/lib/python3.11/site-packages/sklearn/base.py:458: UserWarning:\n",
      "\n",
      "X has feature names, but SVC was fitted without feature names\n",
      "\n"
     ]
    },
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "displaylogo": false,
        "modeBarButtonsToRemove": [
         "sendDataToCloud",
         "lasso2d",
         "autoScale2d",
         "select2d",
         "zoom2d",
         "pan2d",
         "zoomIn2d",
         "zoomOut2d",
         "resetScale2d",
         "toggleSpikelines",
         "hoverCompareCartesian",
         "hoverClosestCartesian"
        ],
        "plotlyServerURL": "https://plot.ly",
        "staticPlot": false,
        "toImageButtonOptions": {
         "height": null,
         "width": null
        }
       },
       "data": [
        {
         "base": 0.5513653713068212,
         "hoverinfo": "text",
         "hoverlabel": {
          "bgcolor": "rgba(0,0,0,0.8)"
         },
         "hovertext": [
          "Model: SVMModel loss after<br>variable: 0 is permuted: 0.651<br>Drop-out loss change: +0.1",
          "Model: SVMModel loss after<br>variable: 4 is permuted: 0.558<br>Drop-out loss change: +0.007",
          "Model: SVMModel loss after<br>variable: 3 is permuted: 0.553<br>Drop-out loss change: +0.001",
          "Model: SVMModel loss after<br>variable: 2 is permuted: 0.539<br>Drop-out loss change: -0.012",
          "Model: SVMModel loss after<br>variable: 1 is permuted: 0.339<br>Drop-out loss change: -0.213"
         ],
         "marker": {
          "color": "#46bac2"
         },
         "orientation": "h",
         "showlegend": false,
         "text": [
          "+0.1",
          "+0.007",
          "+0.001",
          "0.012",
          "0.213"
         ],
         "textposition": "outside",
         "type": "bar",
         "x": [
          0.09989264099795081,
          0.006933968647595989,
          0.0012679020215875525,
          -0.012353175093655189,
          -0.21268905172451402
         ],
         "xaxis": "x",
         "y": [
          "0",
          "4",
          "3",
          "2",
          "1"
         ],
         "yaxis": "y"
        }
       ],
       "layout": {
        "annotations": [
         {
          "font": {
           "size": 16
          },
          "showarrow": false,
          "text": "SVMModel",
          "x": 0.5,
          "xanchor": "center",
          "xref": "paper",
          "y": 1,
          "yanchor": "bottom",
          "yref": "paper"
         },
         {
          "font": {
           "size": 16
          },
          "showarrow": false,
          "text": "drop-out loss",
          "x": 0.5,
          "xanchor": "center",
          "xref": "paper",
          "y": 0,
          "yanchor": "top",
          "yref": "paper",
          "yshift": -30
         }
        ],
        "font": {
         "color": "#371ea3"
        },
        "height": 283,
        "margin": {
         "b": 71,
         "r": 30,
         "t": 78
        },
        "shapes": [
         {
          "line": {
           "color": "#371ea3",
           "dash": "dot",
           "width": 1.5
          },
          "type": "line",
          "x0": 0.5513653713068212,
          "x1": 0.5513653713068212,
          "xref": "x",
          "y0": -1,
          "y1": 5,
          "yref": "y"
         }
        ],
        "template": {
         "data": {
          "scatter": [
           {
            "type": "scatter"
           }
          ]
         }
        },
        "title": {
         "text": "Variable Importance",
         "x": 0.15
        },
        "xaxis": {
         "anchor": "y",
         "automargin": true,
         "domain": [
          0,
          1
         ],
         "fixedrange": true,
         "gridwidth": 2,
         "range": [
          0.2917890656739374,
          0.6981452662131417
         ],
         "tickcolor": "white",
         "ticklen": 3,
         "ticks": "outside",
         "type": "linear",
         "zeroline": false
        },
        "yaxis": {
         "anchor": "x",
         "automargin": true,
         "autorange": "reversed",
         "domain": [
          0,
          1
         ],
         "fixedrange": true,
         "gridwidth": 2,
         "tickcolor": "white",
         "ticklen": 10,
         "ticks": "outside",
         "type": "category"
        }
       }
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "exp.model_parts(loss_function='mae').plot()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "omixhub",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}