3.5 Logistic Regression 002

# 3.5 多クラスロジスティック回帰 Keras 、モデルと学習結果の読み込みと予測

import numpy as np
from keras.models import Sequential
from keras.layers import Dense, Activation
from keras.optimizers import SGD
from sklearn.utils import shuffle
from keras.models import model_from_json

# モデルを読み込む
model = model_from_json(open('my_model35.json').read())

# 学習結果を読み込む
model.load_weights('my_model35.hdf5')

model.summary();

X = np.array([[0, 8], [6, 6], [10, 8], [10, -2]])
prediction = model.predict(X)
print(prediction[0])
print(prediction[1])
print(prediction[2])
print(prediction[3])