{"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)\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":"2021-06-26T20:15:03.521043Z","iopub.execute_input":"2021-06-26T20:15:03.52163Z","iopub.status.idle":"2021-06-26T20:15:03.533511Z","shell.execute_reply.started":"2021-06-26T20:15:03.521514Z","shell.execute_reply":"2021-06-26T20:15:03.532372Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"from sklearn.svm import SVC\nfrom sklearn.ensemble import RandomForestClassifier\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.tree import ExtraTreeClassifier, DecisionTreeClassifier\nfrom sklearn.neural_network import MLPClassifier\nfrom sklearn.neighbors import RadiusNeighborsClassifier\nfrom sklearn.neighbors import KNeighborsClassifier\nfrom sklearn.ensemble import RandomForestClassifier\n\ntrain = pd.read_csv(\"/kaggle/input/digit-recognizer/train.csv\")\ntest = pd.read_csv(\"/kaggle/input/digit-recognizer/test.csv\")\ntrain","metadata":{"execution":{"iopub.status.busy":"2021-06-26T20:15:03.550677Z","iopub.execute_input":"2021-06-26T20:15:03.550938Z","iopub.status.idle":"2021-06-26T20:15:09.598053Z","shell.execute_reply.started":"2021-06-26T20:15:03.550915Z","shell.execute_reply":"2021-06-26T20:15:09.597292Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"x = train.iloc[:, 1:]\ny = train.iloc[:,0]","metadata":{"execution":{"iopub.status.busy":"2021-06-26T20:15:09.599118Z","iopub.execute_input":"2021-06-26T20:15:09.599344Z","iopub.status.idle":"2021-06-26T20:15:09.603343Z","shell.execute_reply.started":"2021-06-26T20:15:09.599322Z","shell.execute_reply":"2021-06-26T20:15:09.602594Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"x_train, x_test , y_train, y_test = train_test_split(x,y,test_size = 0.01)","metadata":{"execution":{"iopub.status.busy":"2021-06-26T20:15:09.604475Z","iopub.execute_input":"2021-06-26T20:15:09.604677Z","iopub.status.idle":"2021-06-26T20:15:09.791456Z","shell.execute_reply.started":"2021-06-26T20:15:09.604655Z","shell.execute_reply":"2021-06-26T20:15:09.790559Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"test.head()","metadata":{"execution":{"iopub.status.busy":"2021-06-26T20:15:09.792972Z","iopub.execute_input":"2021-06-26T20:15:09.79319Z","iopub.status.idle":"2021-06-26T20:15:09.810642Z","shell.execute_reply.started":"2021-06-26T20:15:09.793168Z","shell.execute_reply":"2021-06-26T20:15:09.809309Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"clf = KNeighborsClassifier()\nclf.fit(x_train, y_train)\nclf.score(x_test,y_test)","metadata":{"execution":{"iopub.status.busy":"2021-06-26T20:15:09.813641Z","iopub.execute_input":"2021-06-26T20:15:09.813903Z","iopub.status.idle":"2021-06-26T20:16:31.122141Z","shell.execute_reply.started":"2021-06-26T20:15:09.813879Z","shell.execute_reply":"2021-06-26T20:16:31.1214Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"z = clf.predict(test)\nz","metadata":{"execution":{"iopub.status.busy":"2021-06-26T20:16:31.125532Z","iopub.execute_input":"2021-06-26T20:16:31.127419Z","iopub.status.idle":"2021-06-26T20:16:31.324456Z","shell.execute_reply.started":"2021-06-26T20:16:31.127381Z","shell.execute_reply":"2021-06-26T20:16:31.323746Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sample = pd.read_csv('/kaggle/input/digit-recognizer/sample_submission.csv')\nsample","metadata":{"execution":{"iopub.status.busy":"2021-06-26T20:16:31.329028Z","iopub.execute_input":"2021-06-26T20:16:31.331089Z","iopub.status.idle":"2021-06-26T20:16:31.371694Z","shell.execute_reply.started":"2021-06-26T20:16:31.329528Z","shell.execute_reply":"2021-06-26T20:16:31.370929Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"submission = pd.DataFrame({'TmageTd': list(test.index + 1),'Label':clf.predict(test)})\nsubmission.to_csv('mnist submission.csv',index = False)","metadata":{"execution":{"iopub.status.busy":"2021-06-26T20:16:31.376296Z","iopub.execute_input":"2021-06-26T20:16:31.378704Z","iopub.status.idle":"2021-06-26T20:16:31.651978Z","shell.execute_reply.started":"2021-06-26T20:16:31.376881Z","shell.execute_reply":"2021-06-26T20:16:31.651176Z"},"trusted":true},"execution_count":null,"outputs":[]}]}