8. S-KNN.ipynb

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      "Iris Data set loaded...\n",
      "Label 0 - setosa\n",
      "Label 1 - versicolor\n",
      "Label 2 - virginica\n",
      "Results of Classification using K-nn with K=5 \n",
      " Sample: [5.1 3.7 1.5 0.4]  Actual-label: 0  Predicted-label: 0\n",
      "Classification Accuracy : 1.0\n",
      " Sample: [6.8 3.2 5.9 2.3]  Actual-label: 2  Predicted-label: 2\n",
      "Classification Accuracy : 1.0\n",
      " Sample: [7.2 3.6 6.1 2.5]  Actual-label: 2  Predicted-label: 2\n",
      "Classification Accuracy : 1.0\n",
      " Sample: [6.5 2.8 4.6 1.5]  Actual-label: 1  Predicted-label: 1\n",
      "Classification Accuracy : 1.0\n",
      " Sample: [7.9 3.8 6.4 2. ]  Actual-label: 2  Predicted-label: 2\n",
      "Classification Accuracy : 1.0\n",
      " Sample: [4.6 3.2 1.4 0.2]  Actual-label: 0  Predicted-label: 0\n",
      "Classification Accuracy : 1.0\n",
      " Sample: [5.  3.3 1.4 0.2]  Actual-label: 0  Predicted-label: 0\n",
      "Classification Accuracy : 1.0\n",
      " Sample: [7.7 3.8 6.7 2.2]  Actual-label: 2  Predicted-label: 2\n",
      "Classification Accuracy : 1.0\n",
      " Sample: [5.  3.  1.6 0.2]  Actual-label: 0  Predicted-label: 0\n",
      "Classification Accuracy : 1.0\n",
      " Sample: [6.3 3.3 4.7 1.6]  Actual-label: 1  Predicted-label: 1\n",
      "Classification Accuracy : 1.0\n",
      " Sample: [4.6 3.1 1.5 0.2]  Actual-label: 0  Predicted-label: 0\n",
      "Classification Accuracy : 1.0\n",
      " Sample: [6.5 3.  5.5 1.8]  Actual-label: 2  Predicted-label: 2\n",
      "Classification Accuracy : 1.0\n",
      " Sample: [6.4 3.2 4.5 1.5]  Actual-label: 1  Predicted-label: 1\n",
      "Classification Accuracy : 1.0\n",
      " Sample: [6.1 2.9 4.7 1.4]  Actual-label: 1  Predicted-label: 1\n",
      "Classification Accuracy : 1.0\n",
      " Sample: [7.  3.2 4.7 1.4]  Actual-label: 1  Predicted-label: 1\n",
      "Classification Accuracy : 1.0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\anaconda\\lib\\site-packages\\sklearn\\neighbors\\_classification.py:228: FutureWarning: Unlike other reduction functions (e.g. `skew`, `kurtosis`), the default behavior of `mode` typically preserves the axis it acts along. In SciPy 1.11.0, this behavior will change: the default value of `keepdims` will become False, the `axis` over which the statistic is taken will be eliminated, and the value None will no longer be accepted. Set `keepdims` to True or False to avoid this warning.\n",
      "  mode, _ = stats.mode(_y[neigh_ind, k], axis=1)\n",
      "D:\\anaconda\\lib\\site-packages\\sklearn\\neighbors\\_classification.py:228: FutureWarning: Unlike other reduction functions (e.g. `skew`, `kurtosis`), the default behavior of `mode` typically preserves the axis it acts along. In SciPy 1.11.0, this behavior will change: the default value of `keepdims` will become False, the `axis` over which the statistic is taken will be eliminated, and the value None will no longer be accepted. Set `keepdims` to True or False to avoid this warning.\n",
      "  mode, _ = stats.mode(_y[neigh_ind, k], axis=1)\n",
      "D:\\anaconda\\lib\\site-packages\\sklearn\\neighbors\\_classification.py:228: FutureWarning: Unlike other reduction functions (e.g. `skew`, `kurtosis`), the default behavior of `mode` typically preserves the axis it acts along. In SciPy 1.11.0, this behavior will change: the default value of `keepdims` will become False, the `axis` over which the statistic is taken will be eliminated, and the value None will no longer be accepted. Set `keepdims` to True or False to avoid this warning.\n",
      "  mode, _ = stats.mode(_y[neigh_ind, k], axis=1)\n",
      "D:\\anaconda\\lib\\site-packages\\sklearn\\neighbors\\_classification.py:228: FutureWarning: Unlike other reduction functions (e.g. `skew`, `kurtosis`), the default behavior of `mode` typically preserves the axis it acts along. In SciPy 1.11.0, this behavior will change: the default value of `keepdims` will become False, the `axis` over which the statistic is taken will be eliminated, and the value None will no longer be accepted. Set `keepdims` to True or False to avoid this warning.\n",
      "  mode, _ = stats.mode(_y[neigh_ind, k], axis=1)\n",
      "D:\\anaconda\\lib\\site-packages\\sklearn\\neighbors\\_classification.py:228: FutureWarning: Unlike other reduction functions (e.g. `skew`, `kurtosis`), the default behavior of `mode` typically preserves the axis it acts along. In SciPy 1.11.0, this behavior will change: the default value of `keepdims` will become False, the `axis` over which the statistic is taken will be eliminated, and the value None will no longer be accepted. Set `keepdims` to True or False to avoid this warning.\n",
      "  mode, _ = stats.mode(_y[neigh_ind, k], axis=1)\n",
      "D:\\anaconda\\lib\\site-packages\\sklearn\\neighbors\\_classification.py:228: FutureWarning: Unlike other reduction functions (e.g. `skew`, `kurtosis`), the default behavior of `mode` typically preserves the axis it acts along. In SciPy 1.11.0, this behavior will change: the default value of `keepdims` will become False, the `axis` over which the statistic is taken will be eliminated, and the value None will no longer be accepted. Set `keepdims` to True or False to avoid this warning.\n",
      "  mode, _ = stats.mode(_y[neigh_ind, k], axis=1)\n",
      "D:\\anaconda\\lib\\site-packages\\sklearn\\neighbors\\_classification.py:228: FutureWarning: Unlike other reduction functions (e.g. `skew`, `kurtosis`), the default behavior of `mode` typically preserves the axis it acts along. In SciPy 1.11.0, this behavior will change: the default value of `keepdims` will become False, the `axis` over which the statistic is taken will be eliminated, and the value None will no longer be accepted. Set `keepdims` to True or False to avoid this warning.\n",
      "  mode, _ = stats.mode(_y[neigh_ind, k], axis=1)\n",
      "D:\\anaconda\\lib\\site-packages\\sklearn\\neighbors\\_classification.py:228: FutureWarning: Unlike other reduction functions (e.g. `skew`, `kurtosis`), the default behavior of `mode` typically preserves the axis it acts along. In SciPy 1.11.0, this behavior will change: the default value of `keepdims` will become False, the `axis` over which the statistic is taken will be eliminated, and the value None will no longer be accepted. Set `keepdims` to True or False to avoid this warning.\n",
      "  mode, _ = stats.mode(_y[neigh_ind, k], axis=1)\n",
      "D:\\anaconda\\lib\\site-packages\\sklearn\\neighbors\\_classification.py:228: FutureWarning: Unlike other reduction functions (e.g. `skew`, `kurtosis`), the default behavior of `mode` typically preserves the axis it acts along. In SciPy 1.11.0, this behavior will change: the default value of `keepdims` will become False, the `axis` over which the statistic is taken will be eliminated, and the value None will no longer be accepted. Set `keepdims` to True or False to avoid this warning.\n",
      "  mode, _ = stats.mode(_y[neigh_ind, k], axis=1)\n",
      "D:\\anaconda\\lib\\site-packages\\sklearn\\neighbors\\_classification.py:228: FutureWarning: Unlike other reduction functions (e.g. `skew`, `kurtosis`), the default behavior of `mode` typically preserves the axis it acts along. In SciPy 1.11.0, this behavior will change: the default value of `keepdims` will become False, the `axis` over which the statistic is taken will be eliminated, and the value None will no longer be accepted. Set `keepdims` to True or False to avoid this warning.\n",
      "  mode, _ = stats.mode(_y[neigh_ind, k], axis=1)\n",
      "D:\\anaconda\\lib\\site-packages\\sklearn\\neighbors\\_classification.py:228: FutureWarning: Unlike other reduction functions (e.g. `skew`, `kurtosis`), the default behavior of `mode` typically preserves the axis it acts along. In SciPy 1.11.0, this behavior will change: the default value of `keepdims` will become False, the `axis` over which the statistic is taken will be eliminated, and the value None will no longer be accepted. Set `keepdims` to True or False to avoid this warning.\n",
      "  mode, _ = stats.mode(_y[neigh_ind, k], axis=1)\n",
      "D:\\anaconda\\lib\\site-packages\\sklearn\\neighbors\\_classification.py:228: FutureWarning: Unlike other reduction functions (e.g. `skew`, `kurtosis`), the default behavior of `mode` typically preserves the axis it acts along. In SciPy 1.11.0, this behavior will change: the default value of `keepdims` will become False, the `axis` over which the statistic is taken will be eliminated, and the value None will no longer be accepted. Set `keepdims` to True or False to avoid this warning.\n",
      "  mode, _ = stats.mode(_y[neigh_ind, k], axis=1)\n",
      "D:\\anaconda\\lib\\site-packages\\sklearn\\neighbors\\_classification.py:228: FutureWarning: Unlike other reduction functions (e.g. `skew`, `kurtosis`), the default behavior of `mode` typically preserves the axis it acts along. In SciPy 1.11.0, this behavior will change: the default value of `keepdims` will become False, the `axis` over which the statistic is taken will be eliminated, and the value None will no longer be accepted. Set `keepdims` to True or False to avoid this warning.\n",
      "  mode, _ = stats.mode(_y[neigh_ind, k], axis=1)\n",
      "D:\\anaconda\\lib\\site-packages\\sklearn\\neighbors\\_classification.py:228: FutureWarning: Unlike other reduction functions (e.g. `skew`, `kurtosis`), the default behavior of `mode` typically preserves the axis it acts along. In SciPy 1.11.0, this behavior will change: the default value of `keepdims` will become False, the `axis` over which the statistic is taken will be eliminated, and the value None will no longer be accepted. Set `keepdims` to True or False to avoid this warning.\n",
      "  mode, _ = stats.mode(_y[neigh_ind, k], axis=1)\n",
      "D:\\anaconda\\lib\\site-packages\\sklearn\\neighbors\\_classification.py:228: FutureWarning: Unlike other reduction functions (e.g. `skew`, `kurtosis`), the default behavior of `mode` typically preserves the axis it acts along. In SciPy 1.11.0, this behavior will change: the default value of `keepdims` will become False, the `axis` over which the statistic is taken will be eliminated, and the value None will no longer be accepted. Set `keepdims` to True or False to avoid this warning.\n",
      "  mode, _ = stats.mode(_y[neigh_ind, k], axis=1)\n",
      "D:\\anaconda\\lib\\site-packages\\sklearn\\neighbors\\_classification.py:228: FutureWarning: Unlike other reduction functions (e.g. `skew`, `kurtosis`), the default behavior of `mode` typically preserves the axis it acts along. In SciPy 1.11.0, this behavior will change: the default value of `keepdims` will become False, the `axis` over which the statistic is taken will be eliminated, and the value None will no longer be accepted. Set `keepdims` to True or False to avoid this warning.\n",
      "  mode, _ = stats.mode(_y[neigh_ind, k], axis=1)\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import train_test_split \n",
    "from sklearn.neighbors import KNeighborsClassifier \n",
    "from sklearn import datasets\n",
    "iris=datasets.load_iris() \n",
    "print(\"Iris Data set loaded...\")\n",
    "x_train, x_test, y_train, y_test = train_test_split(iris.data,iris.target,test_size=0.1)\n",
    "#random_state=0\n",
    "for i in range(len(iris.target_names)):\n",
    "    print(\"Label\", i , \"-\",str(iris.target_names[i]))\n",
    "classifier = KNeighborsClassifier(n_neighbors=5)\n",
    "classifier.fit(x_train, y_train)\n",
    "y_pred=classifier.predict(x_test)\n",
    "print(\"Results of Classification using K-nn with K=5 \") \n",
    "for r in range(0,len(x_test)):\n",
    "    print(\" Sample:\", str(x_test[r]), \" Actual-label:\", str(y_test[r]),\" Predicted-label:\", str(y_pred[r]))\n",
    "\n",
    "    print(\"Classification Accuracy :\" , classifier.score(x_test,y_test));\n"
   ]
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   "cell_type": "code",
   "execution_count": null,
   "id": "f6c6d09d",
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