{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"import numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as pt\nfrom sklearn.tree import DecisionTreeClassifier\n\ndata = pd.read_csv(\"../input/digit-recognizer/train.csv\").as_matrix()\nclf=DecisionTreeClassifier()\n\nxtrain=data[0:21000,1:]\ntrain_label=data[0:21000,0]\n\nclf.fit(xtrain,train_label)\n\nxtest=data[0:21000,1:]\nactual_label=data[0:21000,0]\n\nd=xtest[12]\nd.shape=(28,28)\npt.imshow(255-d,cmap='gray')\nprint(clf.predict([xtest[12]]))\npt.show()\n\nd=xtest[9]\nd.shape=(28,28)\npt.imshow(255-d,cmap='gray')\nprint(clf.predict([xtest[9]]))\npt.show()\n\nd=xtest[8]\nd.shape=(28,28)\npt.imshow(255-d,cmap='gray')\nprint(clf.predict([xtest[8]]))\npt.show()\n\nd=xtest[6]\nd.shape=(28,28)\npt.imshow(255-d,cmap='gray')\nprint(clf.predict([xtest[6]]))\npt.show()\n","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":4}