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dhavalsaysdhavalsays
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Fixed an issue in one hot encoding tutorial
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‎ML/5_one_hot_encoding/one_hot_encoding.ipynb‎

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},
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{
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"cell_type": "code",
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"metadata": {
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"collapsed": true
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"cell_type": "code",
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"execution_count": 10,
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"outputs": [
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{
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"12 robinsville 3600 695000"
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"12 0 1 0"
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"12 robinsville 3600 695000 0 1 0"
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"12 3600 695000 0 1 0"
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"12 3600 695000 0 1"
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]
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},
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"execution_count": 14,
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"metadata": {},
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"output_type": "execute_result"
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},
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{
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"cell_type": "code",
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"execution_count": 214,
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"execution_count": 15,
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"metadata": {},
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"outputs": [
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{
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"LinearRegression(copy_X=True, fit_intercept=True, n_jobs=1, normalize=False)"
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]
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},
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"execution_count": 214,
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"execution_count": 15,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"X = df_dummies.drop('price',axis='columns')\n",
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"y = df_dummies.price\n",
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"\n",
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"from sklearn.linear_model import LinearRegression\n",
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"model = LinearRegression()\n",
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"model.fit(X,y)"
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]
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},
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"cell_type": "code",
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"12 3600 0 1"
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" 692293.59277574])"
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]
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},
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{
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"0.95739290372218733"
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},
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{
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"array([ 681241.66845839])"
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]
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},
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},
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"execution_count": 20,
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{
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"array([ 590775.63964739])"
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"cell_type": "code",
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"from sklearn.preprocessing import LabelEncoder\n",
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"cell_type": "code",
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" [ 1, 3600]], dtype=int64)"
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" 710000, 575000, 600000, 620000, 695000], dtype=int64)"
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" 3.60000000e+03]])"
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