# https://machinelearningmastery.com/tutorial-first-neural-network-python-keras/
from keras.models import Sequential
from keras.layers import Dense
import numpy
# fix random seed for reproducibility
numpy.random.seed(7)
#load pima indians dataset
dataset = numpy.loadtxt("pima-indians-diabetes.data", delimiter=",")
# split into input (X) and output (Y) variables
X = dataset[:,0:8]
Y = dataset[:,8]
# create model
model = Sequential()
model.add(Dense(12, input_dim=8, activation='relu'))
model.add(Dense(8, activation='relu'))
model.add(Dense(1, activation='sigmoid'))
# Compile model
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
# Fit the model
model.fit(X, Y, epochs=150, batch_size=10)
Epoch 1/150 768/768 [==============================] - 1s 2ms/step - loss: 3.7106 - acc: 0.5977 Epoch 2/150 768/768 [==============================] - 0s 358us/step - loss: 0.9376 - acc: 0.5924 Epoch 3/150 768/768 [==============================] - 0s 311us/step - loss: 0.7478 - acc: 0.6445 Epoch 4/150 768/768 [==============================] - 0s 224us/step - loss: 0.7121 - acc: 0.6549 Epoch 5/150 768/768 [==============================] - 0s 174us/step - loss: 0.6842 - acc: 0.6680 Epoch 6/150 768/768 [==============================] - 0s 257us/step - loss: 0.6522 - acc: 0.6797 Epoch 7/150 768/768 [==============================] - 0s 254us/step - loss: 0.6496 - acc: 0.6836 Epoch 8/150 768/768 [==============================] - 0s 307us/step - loss: 0.6380 - acc: 0.6875 Epoch 9/150 768/768 [==============================] - 0s 215us/step - loss: 0.6238 - acc: 0.6953 Epoch 10/150 768/768 [==============================] - 0s 184us/step - loss: 0.6288 - acc: 0.6771 Epoch 11/150 768/768 [==============================] - 0s 316us/step - loss: 0.6433 - acc: 0.6745 Epoch 12/150 768/768 [==============================] - 0s 273us/step - loss: 0.6400 - acc: 0.6732 Epoch 13/150 768/768 [==============================] - 0s 241us/step - loss: 0.6262 - acc: 0.6719 Epoch 14/150 768/768 [==============================] - 0s 302us/step - loss: 0.6179 - acc: 0.7018 Epoch 15/150 768/768 [==============================] - 0s 327us/step - loss: 0.6020 - acc: 0.6953 Epoch 16/150 768/768 [==============================] - 0s 244us/step - loss: 0.5877 - acc: 0.7018 Epoch 17/150 768/768 [==============================] - 0s 277us/step - loss: 0.5848 - acc: 0.6992 Epoch 18/150 768/768 [==============================] - 0s 202us/step - loss: 0.6008 - acc: 0.6849 Epoch 19/150 768/768 [==============================] - 0s 180us/step - loss: 0.5807 - acc: 0.7070 Epoch 20/150 768/768 [==============================] - 0s 275us/step - loss: 0.5811 - acc: 0.7174 Epoch 21/150 768/768 [==============================] - 0s 189us/step - loss: 0.5688 - acc: 0.7161 Epoch 22/150 768/768 [==============================] - 0s 214us/step - loss: 0.5824 - acc: 0.6966 Epoch 23/150 768/768 [==============================] - 0s 197us/step - loss: 0.5743 - acc: 0.7122 Epoch 24/150 768/768 [==============================] - 0s 172us/step - loss: 0.5677 - acc: 0.7344 Epoch 25/150 768/768 [==============================] - 0s 177us/step - loss: 0.5580 - acc: 0.7370 Epoch 26/150 768/768 [==============================] - 0s 197us/step - loss: 0.5708 - acc: 0.7031 Epoch 27/150 768/768 [==============================] - 0s 246us/step - loss: 0.5558 - acc: 0.7214 Epoch 28/150 768/768 [==============================] - 0s 288us/step - loss: 0.5559 - acc: 0.7344 Epoch 29/150 768/768 [==============================] - 0s 323us/step - loss: 0.5742 - acc: 0.7135 Epoch 30/150 768/768 [==============================] - 0s 188us/step - loss: 0.5613 - acc: 0.7214 Epoch 31/150 768/768 [==============================] - 0s 176us/step - loss: 0.5690 - acc: 0.7148 Epoch 32/150 768/768 [==============================] - 0s 171us/step - loss: 0.5655 - acc: 0.7096 Epoch 33/150 768/768 [==============================] - 0s 171us/step - loss: 0.5539 - acc: 0.7174 Epoch 34/150 768/768 [==============================] - 0s 176us/step - loss: 0.5528 - acc: 0.7305 Epoch 35/150 768/768 [==============================] - 0s 288us/step - loss: 0.5540 - acc: 0.7148 Epoch 36/150 768/768 [==============================] - 0s 224us/step - loss: 0.5627 - acc: 0.7096 Epoch 37/150 768/768 [==============================] - 0s 241us/step - loss: 0.5357 - acc: 0.7344 Epoch 38/150 768/768 [==============================] - 0s 301us/step - loss: 0.5459 - acc: 0.7135 Epoch 39/150 768/768 [==============================] - 0s 198us/step - loss: 0.5491 - acc: 0.7227 Epoch 40/150 768/768 [==============================] - 0s 216us/step - loss: 0.5494 - acc: 0.7174 Epoch 41/150 768/768 [==============================] - 0s 340us/step - loss: 0.5454 - acc: 0.7292 Epoch 42/150 768/768 [==============================] - 0s 293us/step - loss: 0.5388 - acc: 0.7396 Epoch 43/150 768/768 [==============================] - 0s 202us/step - loss: 0.5336 - acc: 0.7422 Epoch 44/150 768/768 [==============================] - 0s 329us/step - loss: 0.5353 - acc: 0.7448 Epoch 45/150 768/768 [==============================] - 0s 431us/step - loss: 0.5333 - acc: 0.7578 Epoch 46/150 768/768 [==============================] - 0s 346us/step - loss: 0.5293 - acc: 0.7578 Epoch 47/150 768/768 [==============================] - 0s 230us/step - loss: 0.5340 - acc: 0.7396 Epoch 48/150 768/768 [==============================] - 0s 234us/step - loss: 0.5353 - acc: 0.7370 Epoch 49/150 768/768 [==============================] - 0s 250us/step - loss: 0.5355 - acc: 0.7474 Epoch 50/150 768/768 [==============================] - 0s 251us/step - loss: 0.5275 - acc: 0.7409 Epoch 51/150 768/768 [==============================] - 0s 299us/step - loss: 0.5295 - acc: 0.7474 Epoch 52/150 768/768 [==============================] - 0s 255us/step - loss: 0.5306 - acc: 0.7422 Epoch 53/150 768/768 [==============================] - 0s 266us/step - loss: 0.5377 - acc: 0.7422 Epoch 54/150 768/768 [==============================] - 0s 234us/step - loss: 0.5384 - acc: 0.7279 Epoch 55/150 768/768 [==============================] - 0s 240us/step - loss: 0.5231 - acc: 0.7487 Epoch 56/150 768/768 [==============================] - 0s 237us/step - loss: 0.5281 - acc: 0.7435 Epoch 57/150 768/768 [==============================] - 0s 280us/step - loss: 0.5323 - acc: 0.7383 Epoch 58/150 768/768 [==============================] - 0s 242us/step - loss: 0.5233 - acc: 0.7539 Epoch 59/150 768/768 [==============================] - 0s 245us/step - loss: 0.5130 - acc: 0.7617 Epoch 60/150 768/768 [==============================] - 0s 238us/step - loss: 0.5341 - acc: 0.7370 Epoch 61/150 768/768 [==============================] - 0s 241us/step - loss: 0.5265 - acc: 0.7370 Epoch 62/150 768/768 [==============================] - 0s 232us/step - loss: 0.5177 - acc: 0.7487 Epoch 63/150 768/768 [==============================] - 0s 220us/step - loss: 0.5449 - acc: 0.7357 Epoch 64/150 768/768 [==============================] - 0s 260us/step - loss: 0.5319 - acc: 0.7422 Epoch 65/150 768/768 [==============================] - 0s 246us/step - loss: 0.5236 - acc: 0.7422 Epoch 66/150 768/768 [==============================] - 0s 294us/step - loss: 0.5078 - acc: 0.7487 Epoch 67/150 768/768 [==============================] - 0s 253us/step - loss: 0.5167 - acc: 0.7448 Epoch 68/150 768/768 [==============================] - 0s 253us/step - loss: 0.5143 - acc: 0.7526 Epoch 69/150 768/768 [==============================] - 0s 286us/step - loss: 0.5138 - acc: 0.7500 Epoch 70/150 768/768 [==============================] - 0s 264us/step - loss: 0.5377 - acc: 0.7240 Epoch 71/150 768/768 [==============================] - 0s 280us/step - loss: 0.5180 - acc: 0.7409 Epoch 72/150 768/768 [==============================] - 0s 219us/step - loss: 0.5176 - acc: 0.7448 Epoch 73/150 768/768 [==============================] - 0s 245us/step - loss: 0.5164 - acc: 0.7461 Epoch 74/150 768/768 [==============================] - 0s 221us/step - loss: 0.5108 - acc: 0.7604 Epoch 75/150 768/768 [==============================] - 0s 238us/step - loss: 0.5095 - acc: 0.7617 Epoch 76/150 768/768 [==============================] - 0s 232us/step - loss: 0.5119 - acc: 0.7513 Epoch 77/150 768/768 [==============================] - 0s 296us/step - loss: 0.5169 - acc: 0.7617 Epoch 78/150 768/768 [==============================] - 0s 316us/step - loss: 0.5131 - acc: 0.7474 Epoch 79/150 768/768 [==============================] - 0s 223us/step - loss: 0.5138 - acc: 0.7461 Epoch 80/150 768/768 [==============================] - 0s 259us/step - loss: 0.5105 - acc: 0.7565 Epoch 81/150 768/768 [==============================] - 0s 275us/step - loss: 0.5056 - acc: 0.7695 Epoch 82/150 768/768 [==============================] - 0s 228us/step - loss: 0.5060 - acc: 0.7513 Epoch 83/150 768/768 [==============================] - 0s 238us/step - loss: 0.5030 - acc: 0.7591 Epoch 84/150 768/768 [==============================] - 0s 228us/step - loss: 0.4995 - acc: 0.7526 Epoch 85/150 768/768 [==============================] - 0s 230us/step - loss: 0.5063 - acc: 0.7461 Epoch 86/150 768/768 [==============================] - 0s 210us/step - loss: 0.5064 - acc: 0.7474 Epoch 87/150 768/768 [==============================] - 0s 221us/step - loss: 0.4992 - acc: 0.7526 Epoch 88/150 768/768 [==============================] - 0s 250us/step - loss: 0.5010 - acc: 0.7643 Epoch 89/150 768/768 [==============================] - 0s 216us/step - loss: 0.5045 - acc: 0.7682 Epoch 90/150 768/768 [==============================] - 0s 233us/step - loss: 0.5102 - acc: 0.7513 Epoch 91/150 768/768 [==============================] - 0s 246us/step - loss: 0.5022 - acc: 0.7526 Epoch 92/150 768/768 [==============================] - 0s 286us/step - loss: 0.5057 - acc: 0.7396 Epoch 93/150 768/768 [==============================] - 0s 227us/step - loss: 0.4981 - acc: 0.7656 Epoch 94/150 768/768 [==============================] - 0s 227us/step - loss: 0.4992 - acc: 0.7656 Epoch 95/150 768/768 [==============================] - 0s 258us/step - loss: 0.5040 - acc: 0.7500 Epoch 96/150 768/768 [==============================] - 0s 212us/step - loss: 0.4908 - acc: 0.7669 Epoch 97/150 768/768 [==============================] - 0s 245us/step - loss: 0.5004 - acc: 0.7747 Epoch 98/150 768/768 [==============================] - 0s 210us/step - loss: 0.4905 - acc: 0.7617 Epoch 99/150 768/768 [==============================] - 0s 260us/step - loss: 0.4914 - acc: 0.7630 Epoch 100/150 768/768 [==============================] - 0s 232us/step - loss: 0.4845 - acc: 0.7773 Epoch 101/150 768/768 [==============================] - 0s 217us/step - loss: 0.4897 - acc: 0.7773 Epoch 102/150 768/768 [==============================] - 0s 225us/step - loss: 0.4984 - acc: 0.7578 Epoch 103/150 768/768 [==============================] - 0s 246us/step - loss: 0.4987 - acc: 0.7539 Epoch 104/150 768/768 [==============================] - 0s 212us/step - loss: 0.4918 - acc: 0.7839 Epoch 105/150 768/768 [==============================] - 0s 238us/step - loss: 0.5303 - acc: 0.7422 Epoch 106/150 768/768 [==============================] - 0s 215us/step - loss: 0.4976 - acc: 0.7656 Epoch 107/150 768/768 [==============================] - 0s 233us/step - loss: 0.4922 - acc: 0.7708 Epoch 108/150 768/768 [==============================] - 0s 293us/step - loss: 0.4982 - acc: 0.7695 Epoch 109/150 768/768 [==============================] - 0s 268us/step - loss: 0.4874 - acc: 0.7695 Epoch 110/150 768/768 [==============================] - 0s 194us/step - loss: 0.4906 - acc: 0.7682 Epoch 111/150 768/768 [==============================] - 0s 228us/step - loss: 0.4833 - acc: 0.7812 Epoch 112/150 768/768 [==============================] - 0s 249us/step - loss: 0.4916 - acc: 0.7773 Epoch 113/150 768/768 [==============================] - 0s 309us/step - loss: 0.4938 - acc: 0.7630 Epoch 114/150 768/768 [==============================] - 0s 358us/step - loss: 0.4911 - acc: 0.7604 Epoch 115/150 768/768 [==============================] - 0s 410us/step - loss: 0.4905 - acc: 0.7760 Epoch 116/150 768/768 [==============================] - 0s 327us/step - loss: 0.4944 - acc: 0.7721 Epoch 117/150 768/768 [==============================] - 0s 445us/step - loss: 0.4917 - acc: 0.7604 Epoch 118/150 768/768 [==============================] - 0s 293us/step - loss: 0.4894 - acc: 0.7826 Epoch 119/150 768/768 [==============================] - 0s 203us/step - loss: 0.4829 - acc: 0.7695 Epoch 120/150 768/768 [==============================] - 0s 307us/step - loss: 0.4927 - acc: 0.7786 Epoch 121/150 768/768 [==============================] - 0s 367us/step - loss: 0.4924 - acc: 0.7721 Epoch 122/150 768/768 [==============================] - 0s 194us/step - loss: 0.4862 - acc: 0.7721 Epoch 123/150 768/768 [==============================] - 0s 182us/step - loss: 0.4838 - acc: 0.7656 Epoch 124/150 768/768 [==============================] - 0s 181us/step - loss: 0.4831 - acc: 0.7708 Epoch 125/150 768/768 [==============================] - 0s 184us/step - loss: 0.4874 - acc: 0.7852 Epoch 126/150 768/768 [==============================] - 0s 181us/step - loss: 0.4817 - acc: 0.7786 Epoch 127/150 768/768 [==============================] - 0s 177us/step - loss: 0.4903 - acc: 0.7682 Epoch 128/150 768/768 [==============================] - 0s 172us/step - loss: 0.4721 - acc: 0.7786 Epoch 129/150 768/768 [==============================] - 0s 176us/step - loss: 0.4813 - acc: 0.7721 Epoch 130/150 768/768 [==============================] - 0s 172us/step - loss: 0.4749 - acc: 0.7865 Epoch 131/150 768/768 [==============================] - 0s 172us/step - loss: 0.4815 - acc: 0.7773 Epoch 132/150 768/768 [==============================] - 0s 174us/step - loss: 0.4805 - acc: 0.7839 Epoch 133/150 768/768 [==============================] - 0s 171us/step - loss: 0.4839 - acc: 0.7721 Epoch 134/150 768/768 [==============================] - 0s 174us/step - loss: 0.4837 - acc: 0.7734 Epoch 135/150 768/768 [==============================] - 0s 177us/step - loss: 0.4780 - acc: 0.7773 Epoch 136/150 768/768 [==============================] - 0s 172us/step - loss: 0.4739 - acc: 0.7786 Epoch 137/150 768/768 [==============================] - 0s 173us/step - loss: 0.4673 - acc: 0.7786 Epoch 138/150 768/768 [==============================] - 0s 172us/step - loss: 0.4806 - acc: 0.7839 Epoch 139/150 768/768 [==============================] - 0s 177us/step - loss: 0.4656 - acc: 0.7917 Epoch 140/150 768/768 [==============================] - 0s 172us/step - loss: 0.4834 - acc: 0.7773 Epoch 141/150 768/768 [==============================] - 0s 172us/step - loss: 0.4743 - acc: 0.7839 Epoch 142/150 768/768 [==============================] - 0s 176us/step - loss: 0.4836 - acc: 0.7708 Epoch 143/150 768/768 [==============================] - 0s 310us/step - loss: 0.4769 - acc: 0.7734 Epoch 144/150 768/768 [==============================] - 0s 333us/step - loss: 0.4772 - acc: 0.7747 Epoch 145/150 768/768 [==============================] - 0s 245us/step - loss: 0.4890 - acc: 0.7643 Epoch 146/150 768/768 [==============================] - 0s 229us/step - loss: 0.4942 - acc: 0.7669 Epoch 147/150 768/768 [==============================] - 0s 194us/step - loss: 0.4846 - acc: 0.7773 Epoch 148/150 768/768 [==============================] - 0s 180us/step - loss: 0.4715 - acc: 0.7773 Epoch 149/150 768/768 [==============================] - 0s 181us/step - loss: 0.4752 - acc: 0.7695 Epoch 150/150 768/768 [==============================] - 0s 184us/step - loss: 0.4776 - acc: 0.7721
<keras.callbacks.History at 0x2683b99f630>
# evaluate the model
scores = model.evaluate(X, Y)
print("\n%s: %.2f%%" % (model.metrics_names[1], scores[1]*100))
768/768 [==============================] - 0s 94us/step acc: 79.82%
#all in one cell
# Create your first MLP in Keras
from keras.models import Sequential
from keras.layers import Dense
import numpy
# fix random seed for reproducibility
numpy.random.seed(7)
# load pima indians dataset
dataset = numpy.loadtxt("pima-indians-diabetes.data", delimiter=",")
# split into input (X) and output (Y) variables
X = dataset[:,0:8]
Y = dataset[:,8]
# create model
model = Sequential()
model.add(Dense(12, input_dim=8, activation='relu'))
model.add(Dense(8, activation='relu'))
model.add(Dense(1, activation='sigmoid'))
# Compile model
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
# Fit the model
model.fit(X, Y, epochs=150, batch_size=10)
# evaluate the model
scores = model.evaluate(X, Y)
print("\n%s: %.2f%%" % (model.metrics_names[1], scores[1]*100))
Epoch 1/150 768/768 [==============================] - 1s 2ms/step - loss: 3.7104 - acc: 0.5977 Epoch 2/150 768/768 [==============================] - 0s 411us/step - loss: 0.9374 - acc: 0.5938 Epoch 3/150 768/768 [==============================] - 0s 250us/step - loss: 0.7478 - acc: 0.6445 Epoch 4/150 768/768 [==============================] - 0s 421us/step - loss: 0.7120 - acc: 0.6549 Epoch 5/150 768/768 [==============================] - 0s 333us/step - loss: 0.6839 - acc: 0.6667 Epoch 6/150 768/768 [==============================] - 0s 201us/step - loss: 0.6520 - acc: 0.6771 Epoch 7/150 768/768 [==============================] - 0s 174us/step - loss: 0.6505 - acc: 0.6810 Epoch 8/150 768/768 [==============================] - 0s 188us/step - loss: 0.6392 - acc: 0.6862 Epoch 9/150 768/768 [==============================] - 0s 211us/step - loss: 0.6249 - acc: 0.6953 Epoch 10/150 768/768 [==============================] - 0s 172us/step - loss: 0.6308 - acc: 0.6784 Epoch 11/150 768/768 [==============================] - 0s 178us/step - loss: 0.6498 - acc: 0.6719 Epoch 12/150 768/768 [==============================] - 0s 174us/step - loss: 0.6399 - acc: 0.6758 Epoch 13/150 768/768 [==============================] - 0s 197us/step - loss: 0.6252 - acc: 0.6745 Epoch 14/150 768/768 [==============================] - 0s 185us/step - loss: 0.6177 - acc: 0.7005 Epoch 15/150 768/768 [==============================] - 0s 260us/step - loss: 0.6019 - acc: 0.6953 Epoch 16/150 768/768 [==============================] - 0s 180us/step - loss: 0.5883 - acc: 0.7005 Epoch 17/150 768/768 [==============================] - 0s 171us/step - loss: 0.5838 - acc: 0.6992 Epoch 18/150 768/768 [==============================] - 0s 182us/step - loss: 0.6003 - acc: 0.6875 Epoch 19/150 768/768 [==============================] - 0s 313us/step - loss: 0.5797 - acc: 0.7135 Epoch 20/150 768/768 [==============================] - 0s 305us/step - loss: 0.5794 - acc: 0.7227 Epoch 21/150 768/768 [==============================] - 0s 264us/step - loss: 0.5690 - acc: 0.7148 Epoch 22/150 768/768 [==============================] - 0s 177us/step - loss: 0.5812 - acc: 0.7005 Epoch 23/150 768/768 [==============================] - 0s 171us/step - loss: 0.5739 - acc: 0.7135 Epoch 24/150 768/768 [==============================] - 0s 172us/step - loss: 0.5681 - acc: 0.7331 Epoch 25/150 768/768 [==============================] - 0s 173us/step - loss: 0.5573 - acc: 0.7357 Epoch 26/150 768/768 [==============================] - 0s 172us/step - loss: 0.5707 - acc: 0.7018 Epoch 27/150 768/768 [==============================] - 0s 171us/step - loss: 0.5557 - acc: 0.7253 Epoch 28/150 768/768 [==============================] - 0s 173us/step - loss: 0.5553 - acc: 0.7318 Epoch 29/150 768/768 [==============================] - 0s 188us/step - loss: 0.5738 - acc: 0.7201 Epoch 30/150 768/768 [==============================] - 0s 172us/step - loss: 0.5611 - acc: 0.7227 Epoch 31/150 768/768 [==============================] - 0s 172us/step - loss: 0.5681 - acc: 0.7174 Epoch 32/150 768/768 [==============================] - 0s 177us/step - loss: 0.5637 - acc: 0.7161 Epoch 33/150 768/768 [==============================] - 0s 174us/step - loss: 0.5515 - acc: 0.7214 Epoch 34/150 768/768 [==============================] - 0s 173us/step - loss: 0.5510 - acc: 0.7331 Epoch 35/150 768/768 [==============================] - 0s 178us/step - loss: 0.5508 - acc: 0.7240 Epoch 36/150 768/768 [==============================] - 0s 335us/step - loss: 0.5597 - acc: 0.7057 Epoch 37/150 768/768 [==============================] - 0s 220us/step - loss: 0.5371 - acc: 0.7331 Epoch 38/150 768/768 [==============================] - 0s 177us/step - loss: 0.5406 - acc: 0.7227 Epoch 39/150 768/768 [==============================] - 0s 171us/step - loss: 0.5447 - acc: 0.7214 Epoch 40/150 768/768 [==============================] - 0s 174us/step - loss: 0.5439 - acc: 0.7240 Epoch 41/150 768/768 [==============================] - 0s 290us/step - loss: 0.5435 - acc: 0.7357 Epoch 42/150 768/768 [==============================] - 0s 223us/step - loss: 0.5363 - acc: 0.7370 Epoch 43/150 768/768 [==============================] - 0s 210us/step - loss: 0.5320 - acc: 0.7513 Epoch 44/150 768/768 [==============================] - 0s 174us/step - loss: 0.5325 - acc: 0.7396 Epoch 45/150 768/768 [==============================] - 0s 174us/step - loss: 0.5308 - acc: 0.7539 Epoch 46/150 768/768 [==============================] - 0s 210us/step - loss: 0.5292 - acc: 0.7500 Epoch 47/150 768/768 [==============================] - 0s 197us/step - loss: 0.5329 - acc: 0.7357 Epoch 48/150 768/768 [==============================] - 0s 220us/step - loss: 0.5326 - acc: 0.7448 Epoch 49/150 768/768 [==============================] - 0s 276us/step - loss: 0.5327 - acc: 0.7500 Epoch 50/150 768/768 [==============================] - 0s 182us/step - loss: 0.5270 - acc: 0.7396 Epoch 51/150 768/768 [==============================] - 0s 276us/step - loss: 0.5271 - acc: 0.7500 Epoch 52/150 768/768 [==============================] - 0s 346us/step - loss: 0.5286 - acc: 0.7448 Epoch 53/150 768/768 [==============================] - 0s 240us/step - loss: 0.5378 - acc: 0.7435 Epoch 54/150 768/768 [==============================] - 0s 174us/step - loss: 0.5365 - acc: 0.7318 Epoch 55/150 768/768 [==============================] - 0s 172us/step - loss: 0.5221 - acc: 0.7500 Epoch 56/150 768/768 [==============================] - 0s 172us/step - loss: 0.5292 - acc: 0.7409 Epoch 57/150 768/768 [==============================] - 0s 309us/step - loss: 0.5305 - acc: 0.7370 Epoch 58/150 768/768 [==============================] - 0s 331us/step - loss: 0.5231 - acc: 0.7513 Epoch 59/150 768/768 [==============================] - 0s 302us/step - loss: 0.5121 - acc: 0.7630 Epoch 60/150 768/768 [==============================] - 0s 357us/step - loss: 0.5331 - acc: 0.7331 Epoch 61/150 768/768 [==============================] - 0s 448us/step - loss: 0.5277 - acc: 0.7383 Epoch 62/150 768/768 [==============================] - 0s 290us/step - loss: 0.5173 - acc: 0.7565 Epoch 63/150 768/768 [==============================] - 0s 258us/step - loss: 0.5453 - acc: 0.7331 Epoch 64/150 768/768 [==============================] - 0s 241us/step - loss: 0.5307 - acc: 0.7448 Epoch 65/150 768/768 [==============================] - 0s 228us/step - loss: 0.5197 - acc: 0.7474 Epoch 66/150 768/768 [==============================] - 0s 257us/step - loss: 0.5057 - acc: 0.7500 Epoch 67/150 768/768 [==============================] - 0s 247us/step - loss: 0.5159 - acc: 0.7422 Epoch 68/150 768/768 [==============================] - 0s 212us/step - loss: 0.5139 - acc: 0.7565 Epoch 69/150 768/768 [==============================] - 0s 257us/step - loss: 0.5119 - acc: 0.7513 Epoch 70/150 768/768 [==============================] - 0s 266us/step - loss: 0.5364 - acc: 0.7188 Epoch 71/150 768/768 [==============================] - 0s 233us/step - loss: 0.5171 - acc: 0.7396 Epoch 72/150 768/768 [==============================] - 0s 241us/step - loss: 0.5171 - acc: 0.7513 Epoch 73/150 768/768 [==============================] - 0s 246us/step - loss: 0.5161 - acc: 0.7500 Epoch 74/150 768/768 [==============================] - 0s 224us/step - loss: 0.5096 - acc: 0.7604 Epoch 75/150 768/768 [==============================] - 0s 259us/step - loss: 0.5089 - acc: 0.7578 Epoch 76/150 768/768 [==============================] - 0s 228us/step - loss: 0.5100 - acc: 0.7526 Epoch 77/150 768/768 [==============================] - 0s 238us/step - loss: 0.5152 - acc: 0.7604 Epoch 78/150 768/768 [==============================] - 0s 297us/step - loss: 0.5117 - acc: 0.7500 Epoch 79/150 768/768 [==============================] - 0s 267us/step - loss: 0.5129 - acc: 0.7448 Epoch 80/150 768/768 [==============================] - 0s 225us/step - loss: 0.5107 - acc: 0.7578 Epoch 81/150 768/768 [==============================] - 0s 266us/step - loss: 0.5062 - acc: 0.7669 Epoch 82/150 768/768 [==============================] - 0s 270us/step - loss: 0.5038 - acc: 0.7539 Epoch 83/150 768/768 [==============================] - 0s 241us/step - loss: 0.4990 - acc: 0.7591 Epoch 84/150 768/768 [==============================] - 0s 258us/step - loss: 0.4976 - acc: 0.7591 Epoch 85/150 768/768 [==============================] - 0s 237us/step - loss: 0.5046 - acc: 0.7487 Epoch 86/150 768/768 [==============================] - 0s 228us/step - loss: 0.5052 - acc: 0.7487 Epoch 87/150 768/768 [==============================] - 0s 232us/step - loss: 0.4980 - acc: 0.7565 Epoch 88/150 768/768 [==============================] - 0s 309us/step - loss: 0.5011 - acc: 0.7604 Epoch 89/150 768/768 [==============================] - 0s 281us/step - loss: 0.5046 - acc: 0.7734 Epoch 90/150 768/768 [==============================] - 0s 220us/step - loss: 0.5077 - acc: 0.7552 Epoch 91/150 768/768 [==============================] - 0s 236us/step - loss: 0.5025 - acc: 0.7565 Epoch 92/150 768/768 [==============================] - 0s 227us/step - loss: 0.5046 - acc: 0.7448 Epoch 93/150 768/768 [==============================] - 0s 238us/step - loss: 0.4970 - acc: 0.7721 Epoch 94/150 768/768 [==============================] - 0s 230us/step - loss: 0.4990 - acc: 0.7656 Epoch 95/150 768/768 [==============================] - 0s 251us/step - loss: 0.5025 - acc: 0.7500 Epoch 96/150 768/768 [==============================] - 0s 236us/step - loss: 0.4905 - acc: 0.7695 Epoch 97/150 768/768 [==============================] - 0s 233us/step - loss: 0.4975 - acc: 0.7747 Epoch 98/150 768/768 [==============================] - 0s 260us/step - loss: 0.4887 - acc: 0.7656 Epoch 99/150 768/768 [==============================] - 0s 234us/step - loss: 0.4900 - acc: 0.7721 Epoch 100/150 768/768 [==============================] - 0s 216us/step - loss: 0.4846 - acc: 0.7760 Epoch 101/150 768/768 [==============================] - 0s 201us/step - loss: 0.4900 - acc: 0.7773 Epoch 102/150 768/768 [==============================] - 0s 221us/step - loss: 0.4988 - acc: 0.7552 Epoch 103/150 768/768 [==============================] - 0s 232us/step - loss: 0.4997 - acc: 0.7565 Epoch 104/150 768/768 [==============================] - 0s 246us/step - loss: 0.4911 - acc: 0.7865 Epoch 105/150 768/768 [==============================] - 0s 249us/step - loss: 0.5291 - acc: 0.7487 Epoch 106/150 768/768 [==============================] - 0s 233us/step - loss: 0.4943 - acc: 0.7747 Epoch 107/150 768/768 [==============================] - 0s 206us/step - loss: 0.4912 - acc: 0.7721 Epoch 108/150 768/768 [==============================] - 0s 225us/step - loss: 0.5003 - acc: 0.7630 Epoch 109/150 768/768 [==============================] - 0s 305us/step - loss: 0.4852 - acc: 0.7669 Epoch 110/150 768/768 [==============================] - 0s 193us/step - loss: 0.4900 - acc: 0.7656 Epoch 111/150 768/768 [==============================] - 0s 250us/step - loss: 0.4838 - acc: 0.7786 Epoch 112/150 768/768 [==============================] - 0s 241us/step - loss: 0.4958 - acc: 0.7708 Epoch 113/150 768/768 [==============================] - 0s 240us/step - loss: 0.4955 - acc: 0.7604 Epoch 114/150 768/768 [==============================] - 0s 227us/step - loss: 0.4927 - acc: 0.7604 Epoch 115/150 768/768 [==============================] - 0s 199us/step - loss: 0.4912 - acc: 0.7695 Epoch 116/150 768/768 [==============================] - 0s 207us/step - loss: 0.4928 - acc: 0.7721 Epoch 117/150 768/768 [==============================] - 0s 199us/step - loss: 0.4901 - acc: 0.7604 Epoch 118/150 768/768 [==============================] - 0s 186us/step - loss: 0.4889 - acc: 0.7786 Epoch 119/150 768/768 [==============================] - 0s 223us/step - loss: 0.4811 - acc: 0.7630 Epoch 120/150 768/768 [==============================] - 0s 225us/step - loss: 0.4934 - acc: 0.7721 Epoch 121/150 768/768 [==============================] - 0s 185us/step - loss: 0.4924 - acc: 0.7734 Epoch 122/150 768/768 [==============================] - 0s 216us/step - loss: 0.4843 - acc: 0.7826 Epoch 123/150 768/768 [==============================] - 0s 198us/step - loss: 0.4804 - acc: 0.7682 Epoch 124/150 768/768 [==============================] - 0s 211us/step - loss: 0.4831 - acc: 0.7760 Epoch 125/150 768/768 [==============================] - 0s 199us/step - loss: 0.4878 - acc: 0.7812 Epoch 126/150 768/768 [==============================] - 0s 227us/step - loss: 0.4795 - acc: 0.7826 Epoch 127/150 768/768 [==============================] - 0s 199us/step - loss: 0.4900 - acc: 0.7682 Epoch 128/150 768/768 [==============================] - 0s 211us/step - loss: 0.4723 - acc: 0.7721 Epoch 129/150 768/768 [==============================] - 0s 207us/step - loss: 0.4819 - acc: 0.7695 Epoch 130/150 768/768 [==============================] - 0s 219us/step - loss: 0.4749 - acc: 0.7878 Epoch 131/150 768/768 [==============================] - 0s 227us/step - loss: 0.4827 - acc: 0.7656 Epoch 132/150 768/768 [==============================] - 0s 228us/step - loss: 0.4809 - acc: 0.7839 Epoch 133/150 768/768 [==============================] - 0s 216us/step - loss: 0.4828 - acc: 0.7708 Epoch 134/150 768/768 [==============================] - 0s 210us/step - loss: 0.4847 - acc: 0.7747 Epoch 135/150 768/768 [==============================] - 0s 219us/step - loss: 0.4776 - acc: 0.7747 Epoch 136/150 768/768 [==============================] - 0s 201us/step - loss: 0.4738 - acc: 0.7786 Epoch 137/150 768/768 [==============================] - 0s 215us/step - loss: 0.4691 - acc: 0.7773 Epoch 138/150 768/768 [==============================] - 0s 214us/step - loss: 0.4804 - acc: 0.7812 Epoch 139/150 768/768 [==============================] - 0s 228us/step - loss: 0.4651 - acc: 0.7930 Epoch 140/150 768/768 [==============================] - 0s 199us/step - loss: 0.4825 - acc: 0.7826 Epoch 141/150 768/768 [==============================] - 0s 214us/step - loss: 0.4743 - acc: 0.7799 Epoch 142/150 768/768 [==============================] - 0s 249us/step - loss: 0.4843 - acc: 0.7721 Epoch 143/150 768/768 [==============================] - 0s 193us/step - loss: 0.4758 - acc: 0.7734 Epoch 144/150 768/768 [==============================] - 0s 214us/step - loss: 0.4767 - acc: 0.7734 Epoch 145/150 768/768 [==============================] - 0s 220us/step - loss: 0.4900 - acc: 0.7630 Epoch 146/150 768/768 [==============================] - 0s 216us/step - loss: 0.4935 - acc: 0.7669 Epoch 147/150 768/768 [==============================] - 0s 221us/step - loss: 0.4839 - acc: 0.7747 Epoch 148/150 768/768 [==============================] - 0s 220us/step - loss: 0.4724 - acc: 0.7695 Epoch 149/150 768/768 [==============================] - 0s 221us/step - loss: 0.4742 - acc: 0.7682 Epoch 150/150 768/768 [==============================] - 0s 233us/step - loss: 0.4776 - acc: 0.7695 768/768 [==============================] - 0s 134us/step acc: 79.43%
# Create first network with Keras
from keras.models import Sequential
from keras.layers import Dense
import numpy
# fix random seed for reproducibility
seed = 7
numpy.random.seed(seed)
# load pima indians dataset
dataset = numpy.loadtxt("pima-indians-diabetes.data", delimiter=",")
# split into input (X) and output (Y) variables
X = dataset[:,0:8]
Y = dataset[:,8]
# create model
model = Sequential()
model.add(Dense(12, input_dim=8, kernel_initializer='uniform', activation='relu'))
model.add(Dense(8, kernel_initializer='uniform', activation='relu'))
model.add(Dense(1, kernel_initializer='uniform', activation='sigmoid'))
# Compile model
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
# Fit the model
model.fit(X, Y, epochs=150, batch_size=10, verbose=2)
# calculate predictions
predictions = model.predict(X)
# round predictions
rounded = [round(x[0]) for x in predictions]
print(rounded)
Epoch 1/150 - 1s - loss: 0.6771 - acc: 0.6510 Epoch 2/150 - 0s - loss: 0.6586 - acc: 0.6510 Epoch 3/150 - 0s - loss: 0.6470 - acc: 0.6510 Epoch 4/150 - 0s - loss: 0.6393 - acc: 0.6510 Epoch 5/150 - 0s - loss: 0.6320 - acc: 0.6510 Epoch 6/150 - 0s - loss: 0.6188 - acc: 0.6510 Epoch 7/150 - 0s - loss: 0.6194 - acc: 0.6510 Epoch 8/150 - 0s - loss: 0.6135 - acc: 0.6510 Epoch 9/150 - 0s - loss: 0.6087 - acc: 0.6510 Epoch 10/150 - 0s - loss: 0.6164 - acc: 0.6510 Epoch 11/150 - 0s - loss: 0.6052 - acc: 0.6510 Epoch 12/150 - 0s - loss: 0.6034 - acc: 0.6510 Epoch 13/150 - 0s - loss: 0.6004 - acc: 0.6510 Epoch 14/150 - 0s - loss: 0.6033 - acc: 0.6510 Epoch 15/150 - 0s - loss: 0.5989 - acc: 0.6510 Epoch 16/150 - 0s - loss: 0.6000 - acc: 0.6510 Epoch 17/150 - 0s - loss: 0.5995 - acc: 0.6510 Epoch 18/150 - 0s - loss: 0.6007 - acc: 0.6510 Epoch 19/150 - 0s - loss: 0.5972 - acc: 0.6510 Epoch 20/150 - 0s - loss: 0.5982 - acc: 0.6510 Epoch 21/150 - 0s - loss: 0.5950 - acc: 0.6510 Epoch 22/150 - 0s - loss: 0.5936 - acc: 0.6510 Epoch 23/150 - 0s - loss: 0.5930 - acc: 0.6510 Epoch 24/150 - 0s - loss: 0.5989 - acc: 0.6510 Epoch 25/150 - 0s - loss: 0.5956 - acc: 0.6510 Epoch 26/150 - 0s - loss: 0.6006 - acc: 0.6510 Epoch 27/150 - 0s - loss: 0.5949 - acc: 0.6510 Epoch 28/150 - 0s - loss: 0.5905 - acc: 0.6510 Epoch 29/150 - 0s - loss: 0.5927 - acc: 0.6510 Epoch 30/150 - 0s - loss: 0.5909 - acc: 0.6510 Epoch 31/150 - 0s - loss: 0.5900 - acc: 0.6510 Epoch 32/150 - 0s - loss: 0.5903 - acc: 0.6510 Epoch 33/150 - 0s - loss: 0.5844 - acc: 0.6510 Epoch 34/150 - 0s - loss: 0.5894 - acc: 0.6510 Epoch 35/150 - 0s - loss: 0.5916 - acc: 0.6510 Epoch 36/150 - 0s - loss: 0.5834 - acc: 0.6510 Epoch 37/150 - 0s - loss: 0.5824 - acc: 0.6510 Epoch 38/150 - 0s - loss: 0.5923 - acc: 0.6510 Epoch 39/150 - 0s - loss: 0.5833 - acc: 0.6471 Epoch 40/150 - 0s - loss: 0.5869 - acc: 0.6693 Epoch 41/150 - 0s - loss: 0.5820 - acc: 0.6953 Epoch 42/150 - 0s - loss: 0.5807 - acc: 0.7070 Epoch 43/150 - 0s - loss: 0.5787 - acc: 0.7122 Epoch 44/150 - 0s - loss: 0.5865 - acc: 0.7031 Epoch 45/150 - 0s - loss: 0.5788 - acc: 0.7096 Epoch 46/150 - 0s - loss: 0.5774 - acc: 0.7018 Epoch 47/150 - 0s - loss: 0.5782 - acc: 0.7148 Epoch 48/150 - 0s - loss: 0.5752 - acc: 0.7070 Epoch 49/150 - 0s - loss: 0.5744 - acc: 0.7122 Epoch 50/150 - 0s - loss: 0.5740 - acc: 0.7174 Epoch 51/150 - 0s - loss: 0.5731 - acc: 0.7174 Epoch 52/150 - 0s - loss: 0.5706 - acc: 0.7135 Epoch 53/150 - 0s - loss: 0.5729 - acc: 0.7122 Epoch 54/150 - 0s - loss: 0.5707 - acc: 0.7096 Epoch 55/150 - 0s - loss: 0.5728 - acc: 0.7057 Epoch 56/150 - 0s - loss: 0.5710 - acc: 0.7109 Epoch 57/150 - 0s - loss: 0.5678 - acc: 0.7083 Epoch 58/150 - 0s - loss: 0.5725 - acc: 0.7096 Epoch 59/150 - 0s - loss: 0.5668 - acc: 0.7044 Epoch 60/150 - 0s - loss: 0.5690 - acc: 0.7057 Epoch 61/150 - 0s - loss: 0.5662 - acc: 0.7083 Epoch 62/150 - 0s - loss: 0.5680 - acc: 0.7201 Epoch 63/150 - 0s - loss: 0.5712 - acc: 0.7096 Epoch 64/150 - 0s - loss: 0.5658 - acc: 0.7174 Epoch 65/150 - 0s - loss: 0.5630 - acc: 0.7109 Epoch 66/150 - 0s - loss: 0.5588 - acc: 0.7135 Epoch 67/150 - 0s - loss: 0.5586 - acc: 0.7135 Epoch 68/150 - 0s - loss: 0.5603 - acc: 0.7083 Epoch 69/150 - 0s - loss: 0.5559 - acc: 0.7279 Epoch 70/150 - 0s - loss: 0.5609 - acc: 0.7109 Epoch 71/150 - 0s - loss: 0.5571 - acc: 0.7044 Epoch 72/150 - 0s - loss: 0.5556 - acc: 0.7096 Epoch 73/150 - 0s - loss: 0.5501 - acc: 0.7148 Epoch 74/150 - 0s - loss: 0.5577 - acc: 0.6992 Epoch 75/150 - 0s - loss: 0.5540 - acc: 0.7201 Epoch 76/150 - 0s - loss: 0.5508 - acc: 0.7227 Epoch 77/150 - 0s - loss: 0.5504 - acc: 0.7253 Epoch 78/150 - 0s - loss: 0.5465 - acc: 0.7292 Epoch 79/150 - 0s - loss: 0.5498 - acc: 0.7174 Epoch 80/150 - 0s - loss: 0.5448 - acc: 0.7266 Epoch 81/150 - 0s - loss: 0.5427 - acc: 0.7305 Epoch 82/150 - 0s - loss: 0.5529 - acc: 0.7174 Epoch 83/150 - 0s - loss: 0.5524 - acc: 0.7109 Epoch 84/150 - 0s - loss: 0.5451 - acc: 0.7187 Epoch 85/150 - 0s - loss: 0.5465 - acc: 0.7201 Epoch 86/150 - 0s - loss: 0.5498 - acc: 0.7266 Epoch 87/150 - 0s - loss: 0.5405 - acc: 0.7253 Epoch 88/150 - 0s - loss: 0.5399 - acc: 0.7201 Epoch 89/150 - 0s - loss: 0.5583 - acc: 0.7318 Epoch 90/150 - 0s - loss: 0.5416 - acc: 0.7253 Epoch 91/150 - 0s - loss: 0.5391 - acc: 0.7266 Epoch 92/150 - 0s - loss: 0.5405 - acc: 0.7266 Epoch 93/150 - 0s - loss: 0.5402 - acc: 0.7174 Epoch 94/150 - 0s - loss: 0.5392 - acc: 0.7357 Epoch 95/150 - 0s - loss: 0.5359 - acc: 0.7214 Epoch 96/150 - 0s - loss: 0.5413 - acc: 0.7357 Epoch 97/150 - 0s - loss: 0.5401 - acc: 0.7266 Epoch 98/150 - 0s - loss: 0.5332 - acc: 0.7305 Epoch 99/150 - 0s - loss: 0.5274 - acc: 0.7409 Epoch 100/150 - 0s - loss: 0.5339 - acc: 0.7279 Epoch 101/150 - 0s - loss: 0.5313 - acc: 0.7279 Epoch 102/150 - 0s - loss: 0.5323 - acc: 0.7409 Epoch 103/150 - 0s - loss: 0.5404 - acc: 0.7227 Epoch 104/150 - 0s - loss: 0.5351 - acc: 0.7344 Epoch 105/150 - 0s - loss: 0.5287 - acc: 0.7318 Epoch 106/150 - 0s - loss: 0.5291 - acc: 0.7305 Epoch 107/150 - 0s - loss: 0.5335 - acc: 0.7409 Epoch 108/150 - 0s - loss: 0.5314 - acc: 0.7331 Epoch 109/150 - 0s - loss: 0.5269 - acc: 0.7383 Epoch 110/150 - 0s - loss: 0.5249 - acc: 0.7422 Epoch 111/150 - 0s - loss: 0.5323 - acc: 0.7383 Epoch 112/150 - 0s - loss: 0.5241 - acc: 0.7396 Epoch 113/150 - 0s - loss: 0.5236 - acc: 0.7409 Epoch 114/150 - 0s - loss: 0.5257 - acc: 0.7435 Epoch 115/150 - 0s - loss: 0.5204 - acc: 0.7435 Epoch 116/150 - 0s - loss: 0.5213 - acc: 0.7422 Epoch 117/150 - 0s - loss: 0.5189 - acc: 0.7461 Epoch 118/150 - 0s - loss: 0.5240 - acc: 0.7435 Epoch 119/150 - 0s - loss: 0.5125 - acc: 0.7448 Epoch 120/150 - 0s - loss: 0.5154 - acc: 0.7435 Epoch 121/150 - 0s - loss: 0.5159 - acc: 0.7565 Epoch 122/150 - 0s - loss: 0.5131 - acc: 0.7578 Epoch 123/150 - 0s - loss: 0.5104 - acc: 0.7474 Epoch 124/150 - 0s - loss: 0.5059 - acc: 0.7617 Epoch 125/150 - 0s - loss: 0.5067 - acc: 0.7448 Epoch 126/150 - 0s - loss: 0.5088 - acc: 0.7227 Epoch 127/150 - 0s - loss: 0.5109 - acc: 0.7539 Epoch 128/150 - 0s - loss: 0.5037 - acc: 0.7708 Epoch 129/150 - 0s - loss: 0.5129 - acc: 0.7591 Epoch 130/150 - 0s - loss: 0.4990 - acc: 0.7656 Epoch 131/150 - 0s - loss: 0.4970 - acc: 0.7617 Epoch 132/150 - 0s - loss: 0.4951 - acc: 0.7656 Epoch 133/150 - 0s - loss: 0.5020 - acc: 0.7565 Epoch 134/150 - 0s - loss: 0.5000 - acc: 0.7721 Epoch 135/150 - 0s - loss: 0.4927 - acc: 0.7617 Epoch 136/150 - 0s - loss: 0.4975 - acc: 0.7578 Epoch 137/150 - 0s - loss: 0.5046 - acc: 0.7643 Epoch 138/150 - 0s - loss: 0.4963 - acc: 0.7643 Epoch 139/150 - 0s - loss: 0.4869 - acc: 0.7643 Epoch 140/150 - 0s - loss: 0.4884 - acc: 0.7591 Epoch 141/150 - 0s - loss: 0.4879 - acc: 0.7630 Epoch 142/150 - 0s - loss: 0.4911 - acc: 0.7617 Epoch 143/150 - 0s - loss: 0.4841 - acc: 0.7721 Epoch 144/150 - 0s - loss: 0.4856 - acc: 0.7708 Epoch 145/150 - 0s - loss: 0.4869 - acc: 0.7760 Epoch 146/150 - 0s - loss: 0.4883 - acc: 0.7682 Epoch 147/150 - 0s - loss: 0.4831 - acc: 0.7747 Epoch 148/150 - 0s - loss: 0.4880 - acc: 0.7852 Epoch 149/150 - 0s - loss: 0.4779 - acc: 0.7721 Epoch 150/150 - 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