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{ | |
"cells": [ | |
{ | |
"cell_type": "code", | |
"execution_count": 27, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [], | |
"source": [ | |
"passengers_set_1 = titanic_df[titanic_df.pclass == 1].iloc[:20,:].copy()\n", | |
"passengers_set_2 = titanic_df[titanic_df.pclass == 2].iloc[:20,:].copy()\n", | |
"passengers_set_3 = titanic_df[titanic_df.pclass == 3].iloc[:20,:].copy()\n", | |
"passenger_set = pd.concat([passengers_set_1,passengers_set_2,passengers_set_3])\n", | |
"testing_set = preprocess_titanic_df(passenger_set)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 28, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [ | |
"training_set = pd.concat([titanic_df, passenger_set]).drop_duplicates(keep=False)\n", | |
"training_set = preprocess_titanic_df(training_set)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 29, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [], | |
"source": [ | |
"X_train = training_set.drop(['survived'], axis=1).values\n", | |
"y_train = training_set['survived'].values\n", | |
"X_test = testing_set.drop(['survived'], axis=1).values\n", | |
"y_test = testing_set['survived'].values" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 30, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"Step #100, epoch #25, avg. train loss: 0.64422\n", | |
"Step #200, epoch #50, avg. train loss: 0.60906\n", | |
"Step #300, epoch #75, avg. train loss: 0.59641\n", | |
"Step #400, epoch #100, avg. train loss: 0.58298\n", | |
"Step #500, epoch #125, avg. train loss: 0.56000\n", | |
"Step #600, epoch #150, avg. train loss: 0.53058\n", | |
"Step #700, epoch #175, avg. train loss: 0.50669\n", | |
"Step #800, epoch #200, avg. train loss: 0.48891\n", | |
"Step #900, epoch #225, avg. train loss: 0.47792\n", | |
"Step #1000, epoch #250, avg. train loss: 0.46642\n" | |
] | |
}, | |
{ | |
"data": { | |
"text/plain": [ | |
"0.78333333333333333" | |
] | |
}, | |
"execution_count": 30, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"tf_clf_dnn.fit (X_train, y_train)\n", | |
"tf_clf_dnn.score (X_test, y_test)" | |
] | |
} | |
], | |
"metadata": { | |
"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": "3.4.2" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 0 | |
} |
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