classification-12Liner.ipynb

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   "source": [
    "!pip install scikit-learn==0.18"
   ]
  },
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   "source": [
    "import pandas\n",
    "from sklearn.neighbors import KNeighborsClassifier"
   ]
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   "source": [
    "url = \"https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data\"\n",
    "names = ['sepal-length', 'sepal-width', 'petal-length', 'petal-width', 'class']\n",
    "dataset = pandas.read_csv(url, names=names)"
   ]
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   "source": [
    "array = dataset.values\n",
    "X = array[:,0:4]\n",
    "Y = array[:,4]"
   ]
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      "text/plain": [
       "KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\n",
       "           metric_params=None, n_jobs=1, n_neighbors=5, p=2,\n",
       "           weights='uniform')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "knn = KNeighborsClassifier()\n",
    "knn.fit(X, Y)"
   ]
  },
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     "text": [
      "['Iris-versicolor']\n"
     ]
    }
   ],
   "source": [
    "predictions = knn.predict([[6.4,3.2,4.5,1.5]])\n",
    "print(predictions)"
   ]
  },
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