{"cells":[{"metadata":{"id":"K4vm9OxVpDFF","colab_type":"code","colab":{},"trusted":true,"_uuid":"2ed84cd8a5726284c6acdf61892ea47a20081b6e"},"cell_type":"code","source":"import pandas as pd\nimport numpy as np\nfrom sklearn.preprocessing import StandardScaler\nfrom sklearn.neighbors import KNeighborsClassifier\nfrom sklearn import preprocessing\n\ndf_csv = pd.read_csv('../input/train.csv')\nY_train = pd.read_csv('../input/test.csv')\nY=df_csv.label\nX=df_csv.iloc[:,1:]\n\n\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"8e192c1469c90b42b066fc7d3acea076fabd458f"},"cell_type":"code","source":"X = preprocessing.normalize(X)\nx = StandardScaler().fit_transform(X)\n\n\n\nneigh = KNeighborsClassifier(n_neighbors=3,algorithm=\"auto\")\nmodel=neigh.fit(x, Y) \n\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"results = model.predict(Y_train)\n\n\nsubmission = pd.read_csv('../input/sample_submission.csv')\n\nsubmission['Label'] = results\n\n\nsubmission.to_csv('Digit_submission.csv',index=False)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"","execution_count":null,"outputs":[]}],"metadata":{"colab":{"name":"Untitled9.ipynb","version":"0.3.2","provenance":[],"collapsed_sections":[]},"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.6.6","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":1}