{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"import pandas as reader\nimport csv\nimport numpy as number\nfrom sklearn.model_selection import GridSearchCV\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.neighbors import KNeighborsClassifier\n\n# Reading training data set\ntrain = reader.read_csv(\"../input/digit-recognizer/train.csv\")\n\n# Reading Test Data Set\ntest = reader.read_csv(\"../input/digit-recognizer/test.csv\")\n# Setting inputs\ninputData = train.drop(columns=['label'])\n# Setting output\nresult = train['label'].values\n\n# spliting data for training and testing\n# size means n% of dataset will be used for training\ninputTrain, inputTest, resultTrain, resultTest = train_test_split(inputData, result, test_size=0.2, random_state=1,\n                                                                  stratify=result)\n\n# ********* HypterTunning for parameter K ****************\n\n# ********* I have already run it and found value of k which is [1] *********\n# ********* putting them in comments as it will take a lot of time  *********\n\n# knn_K = KNeighborsClassifier()\n# k_range = number.arange(1, 10)\n# knn_hypterTunnig = GridSearchCV(knn_K,{'n_neighbors': k_range}, cv=3)\n# knn_hypterTunnig.fit(inputData, result)\n# print(knn_hypterTunnig.best_params_)\n# print(knn_hypterTunnig.best_score_)\n\nknnClassifier = KNeighborsClassifier(n_neighbors=1, n_jobs=-1)\nknnClassifier.fit(inputData, result)\nres = [[]]\nres.clear()\nimageid =1\nprint(\"Classification has started\")\nprediction = knnClassifier.predict(test)\nprint(prediction)\n\nprint(\"Printing the output\")\n\nfor i in prediction:\n    res.append([imageid,i])\n    imageid=imageid+1\n\nwith open('KNNoutput.csv', 'w', newline='') as file:\n    writer = csv.writer(file)\n    writer.writerows(res)\n","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","collapsed":true,"_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":false},"cell_type":"code","source":"","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}