{"cells":[{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"6f4e8059-357c-04f4-39d0-c1688caa2d82"},"outputs":[],"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 in \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 \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory\n\nfrom subprocess import check_output\nprint(check_output([\"ls\", \"../input\"]).decode(\"utf8\"))\n\n# Any results you write to the current directory are saved as output."},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"31078d7a-9b2f-a3d9-ab70-e3e6f1e69bab"},"outputs":[],"source":"import numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\nfrom sklearn.neural_network import MLPClassifier\n\ntrain=pd.read_csv(\"../input/train.csv\", na_values=\"NA\")\ntest = pd.read_csv(\"../input/test.csv\", na_values=\"NA\")\n\na=((train.loc[:,'label']).as_matrix())\ny=np.zeros(shape=(train.shape[0],10))\n\nfor i in range(0,train.shape[0]):\n    y[i][a[i]]=1\n\ntrain.drop(['label'],axis=1,inplace=True)\nX=pd.concat([train,test])\nx=X.as_matrix()\n#print(np.sum(x[:,0]))\nl=len(x[0])\n\n\"\"\"for i in range(0,l):\n    if (np.sum(x[:,i]==0)):\n        np.delete(x, i, 1)\"\"\"\n\nx_tr=x[:int(train.shape[0]*0.8)]\nx_cv=x[int(train.shape[0]*0.8):train.shape[0]]\nx_test=x[train.shape[0]:]\ny_tr=y[:int(train.shape[0]*0.8)]\ny_cv=y[int(train.shape[0]*0.8):train.shape[0]]\n    \nnn= MLPClassifier(hidden_layer_sizes=(train.shape[1]))"}],"metadata":{"_change_revision":0,"_is_fork":false,"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.6.0"}},"nbformat":4,"nbformat_minor":0}