{"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_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load\n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\nimport numpy as np\n\nimport matplotlib.pyplot as plt\n\nimport pandas as pd\n\n# Input data files are available in the read-only \"../input/\" directory\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))\n\n# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2022-08-22T05:37:05.066673Z","iopub.execute_input":"2022-08-22T05:37:05.067189Z","iopub.status.idle":"2022-08-22T05:37:05.105469Z","shell.execute_reply.started":"2022-08-22T05:37:05.067084Z","shell.execute_reply":"2022-08-22T05:37:05.104325Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train = pd.read_csv(\"/kaggle/input/digit-recognizer/train.csv\")\ntest = pd.read_csv('/kaggle/input/digit-recognizer/test.csv')\nsample = pd.read_csv('/kaggle/input/digit-recognizer/sample_submission.csv')","metadata":{"execution":{"iopub.status.busy":"2022-08-22T05:37:39.903747Z","iopub.execute_input":"2022-08-22T05:37:39.904866Z","iopub.status.idle":"2022-08-22T05:37:45.692509Z","shell.execute_reply.started":"2022-08-22T05:37:39.904817Z","shell.execute_reply":"2022-08-22T05:37:45.691327Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"from sklearn.tree import DecisionTreeClassifier\nclf = DecisionTreeClassifier()","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_data = train.iloc[:, 1:]","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"trainLabel = train.iloc[:,0]","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"clf.fit(train_data, trainLabel)","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#testing data","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"xtest = test.iloc[:,:].to_numpy()\nactual_nums = train.iloc[:, 0]\n","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"d = xtest[10]\n\nd.shape=(28,28)\n\nplt.imshow(255-d, cmap='gray')\nprint(clf.predict([xtest[10]]))\nplt.show()","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"p = clf.predict(xtest)\ncount = 0\n\nimage_ids = sample.iloc[:,0]\n\noutput = pd.DataFrame({'ImageId' : image_ids, 'Label' : p})\noutput.to_csv('submission2.csv', index=False)","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"submission2 = pd.read_csv('submission2.csv')\nsubmission2","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sample","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}