#!/usr/bin/env python
# coding: utf-8

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from keras.layers.core import Dense, Activation
from keras.models import Sequential
from keras.optimizers import Adam
from sklearn import datasets, preprocessing
import numpy as np


# # MNIST - Keras (Backend: TensorFlow)
# 
# 以下のTensorFlowのTutorialと見比べてみて下さい  
# http://www.tensorflow.org/tutorials/mnist/beginners/index.html

# ## MNIST Data

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# データセットの用意
mnist = datasets.fetch_mldata('MNIST original')

X = mnist.data.astype(float)
X /= 255

y = preprocessing.LabelBinarizer().fit_transform(mnist.target)

# 訓練用とテスト用にデータを分割
train_size = 60000

X_train, X_test = np.split(X, [train_size])
y_train, y_test = np.split(y, [train_size])


# ## Implementing the Regression

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model = Sequential()
model.add(Dense(10, input_shape=(784,), init='zero'))
model.add(Activation("softmax"))


# ## Training

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# モデルをコンパイル
model.compile(loss='categorical_crossentropy', optimizer=Adam(lr=0.01))


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model.fit(X_train, y_train, nb_epoch=10, batch_size=100)


# ## Evaluating

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model.evaluate(X_test, y_test, show_accuracy=True)


# Accuracy: 0.9204

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