In [9]:

    

from keras.models import Sequential
from keras.layers import LSTM, Dense, Activation
from keras.optimizers import SGD


    

In [6]:

    

model = Sequential()
model.add(LSTM(5, input_shape=(2, 1)))
model.add(Dense(1))
model.add(Activation('sigmoid'))


    

In [7]:

    

model.compile(optimizer='sgd', loss='mse')


    

In [10]:

    

algorithm = SGD(lr=0.1, momentum=0.3)
model.compile(optimizer=algorithm, loss='mse')


    

In [11]:

    

model.compile(optimizer='sgd', loss='mean_squared_error', metrics=['accuracy'])


    

In [18]:

    

import numpy as np
data = np.array([0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0])


    

In [19]:

    

data


    

    
Out[19]:





array([ 0.1,  0.2,  0.3,  0.4,  0.5,  0.6,  0.7,  0.8,  0.9,  1. ])

In [20]:

    

# (1 sample, 10 time steps, 1 feature) のテンソルに変換
data = data.reshape((1, 10, 1))


    

In [21]:

    

data.shape


    

    
Out[21]:





(1, 10, 1)

In [22]:

    

data = np.array([
    [0.1, 1.0],
    [0.2, 0.9],
    [0.3, 0.8],
    [0.4, 0.7],
    [0.5, 0.6],
    [0.6, 0.5],
    [0.7, 0.4],
    [0.8, 0.3],
    [0.9, 0.2],
    [1.0, 0.1]
])


    

In [23]:

    

data.shape


    

    
Out[23]:





(10, 2)

In [24]:

    

# (1 sample, 10 timesteps, 2 features) のテンソルに変換
data = data.reshape(1, 10, 2)


    

In [25]:

    

data.shape


    

    
Out[25]:





(1, 10, 2)

In [ ]: