28902f94ad3a8853570086f87858ee0b92cf8912
2 from keras
.models
import Sequential
3 from keras
.layers
import Dense
, Dropout
# , Activation
7 model
.add(Dense(26, input_shape
=(13,), activation
='relu'))
8 #model.add(Dense(100, activation='relu'))
9 #model.add(Dropout(0.25))
10 model
.add(Dense(100, activation
='relu'))
11 model
.add(Dense(26, activation
='relu'))
12 model
.add(Dense(1, activation
='sigmoid'))
15 loss
='binary_crossentropy',
21 dat
= np
.genfromtxt('train.txt', dtype
=float, delimiter
='\t', usecols
=range(1, 14))
22 lab
= np
.genfromtxt('train.txt', dtype
=int, delimiter
='\t', usecols
=[0])
24 model
.fit(dat
, lab
, epochs
=10, batch_size
=32)
26 with
open('model.json', 'w') as f
:
27 f
.write(model
.to_json())
28 model
.save_weights('model.hdf5')