第一个神经网络程序实战
作者：互联网
import numpy as np
import pandas as pd
from keras.models import Sequential
from keras.layers import Dense
np.random.seed(10) # 指定乱数种子
# 载入数据集
df = pd.read_csv("D:/Keras/Ch05/diabetes.csv")
dataset = df.values
np.random.shuffle(dataset) # 使用乱数打乱数据
# 分割成输入的训练数据和标签数据
X = dataset[:, 0:8]
Y = dataset[:, 8]
# 定义模型
model = Sequential()
model.add(Dense(10, input_shape=(8,), activation="relu"))
model.add(Dense(8, activation="relu"))
model.add(Dense(1, activation="sigmoid"))
model.summary() # 显示模型摘要信息
#编译模型
model.compile(loss="binary_crossentropy", optimizer="sgd",
metrics=["accuracy"])
# 训练模型
model.fit(X, Y, epochs=150, batch_size=10)
# 评估模型
loss, accuracy = model.evaluate(X, Y)
print("准确度 = {:.2f}".format(accuracy))
输出结果为：
Model: "sequential_1" _________________________________________________________________ Layer (type) Output Shape Param # ================================================================= dense_3 (Dense) (None, 10) 90 _________________________________________________________________ dense_4 (Dense) (None, 8) 88 _________________________________________________________________ dense_5 (Dense) (None, 1) 9 ================================================================= Total params: 187 Trainable params: 187 Non-trainable params: 0 _________________________________________________________________ Epoch 1/150 77/77 [==============================] - 0s 565us/step - loss: 1.5253 - accuracy: 0.6185 Epoch 2/150 77/77 [==============================] - 0s 559us/step - loss: 0.6898 - accuracy: 0.6419 Epoch 3/150 77/77 [==============================] - 0s 562us/step - loss: 0.6524 - accuracy: 0.6510 Epoch 4/150 77/77 [==============================] - 0s 569us/step - loss: 0.6511 - accuracy: 0.6654 Epoch 5/150 77/77 [==============================] - 0s 551us/step - loss: 0.6418 - accuracy: 0.6602 Epoch 6/150 77/77 [==============================] - 0s 517us/step - loss: 0.6401 - accuracy: 0.6562 Epoch 7/150 77/77 [==============================] - 0s 538us/step - loss: 0.6324 - accuracy: 0.6680 Epoch 8/150 77/77 [==============================] - 0s 516us/step - loss: 0.6289 - accuracy: 0.6549 Epoch 9/150 77/77 [==============================] - 0s 520us/step - loss: 0.6264 - accuracy: 0.6732 Epoch 10/150 77/77 [==============================] - 0s 535us/step - loss: 0.6262 - accuracy: 0.6810 Epoch 11/150 77/77 [==============================] - 0s 576us/step - loss: 0.6207 - accuracy: 0.6745 Epoch 12/150 77/77 [==============================] - 0s 552us/step - loss: 0.6194 - accuracy: 0.6628 Epoch 13/150 77/77 [==============================] - 0s 512us/step - loss: 0.6214 - accuracy: 0.6615 Epoch 14/150 77/77 [==============================] - 0s 538us/step - loss: 0.6227 - accuracy: 0.6680 Epoch 15/150 77/77 [==============================] - 0s 556us/step - loss: 0.6210 - accuracy: 0.6628 Epoch 16/150 77/77 [==============================] - 0s 467us/step - loss: 0.6353 - accuracy: 0.6641 Epoch 17/150 77/77 [==============================] - 0s 523us/step - loss: 0.6283 - accuracy: 0.6693 Epoch 18/150 77/77 [==============================] - 0s 525us/step - loss: 0.6269 - accuracy: 0.6680 Epoch 19/150 77/77 [==============================] - 0s 551us/step - loss: 0.6204 - accuracy: 0.6615 Epoch 20/150 77/77 [==============================] - 0s 571us/step - loss: 0.6191 - accuracy: 0.6680 Epoch 21/150 77/77 [==============================] - 0s 567us/step - loss: 0.6166 - accuracy: 0.6706 Epoch 22/150 77/77 [==============================] - 0s 521us/step - loss: 0.6219 - accuracy: 0.6693 Epoch 23/150 77/77 [==============================] - 0s 640us/step - loss: 0.6199 - accuracy: 0.6823 Epoch 24/150 77/77 [==============================] - 0s 551us/step - loss: 0.6170 - accuracy: 0.6641 Epoch 25/150 77/77 [==============================] - 0s 544us/step - loss: 0.6129 - accuracy: 0.6823 Epoch 26/150 77/77 [==============================] - 0s 553us/step - loss: 0.6132 - accuracy: 0.6602 Epoch 27/150 77/77 [==============================] - 0s 499us/step - loss: 0.6150 - accuracy: 0.6758 Epoch 28/150 77/77 [==============================] - 0s 536us/step - loss: 0.6105 - accuracy: 0.6784 Epoch 29/150 77/77 [==============================] - 0s 518us/step - loss: 0.6097 - accuracy: 0.6706 Epoch 30/150 77/77 [==============================] - 0s 512us/step - loss: 0.6135 - accuracy: 0.6823 Epoch 31/150 77/77 [==============================] - 0s 528us/step - loss: 0.6114 - accuracy: 0.6680 Epoch 32/150 77/77 [==============================] - 0s 499us/step - loss: 0.6040 - accuracy: 0.6784 Epoch 33/150 77/77 [==============================] - 0s 514us/step - loss: 0.6050 - accuracy: 0.6771 Epoch 34/150 77/77 [==============================] - 0s 499us/step - loss: 0.6039 - accuracy: 0.6745 Epoch 35/150 77/77 [==============================] - 0s 519us/step - loss: 0.6071 - accuracy: 0.6745 Epoch 36/150 77/77 [==============================] - 0s 635us/step - loss: 0.6013 - accuracy: 0.6849 Epoch 37/150 77/77 [==============================] - 0s 536us/step - loss: 0.6017 - accuracy: 0.6875 Epoch 38/150 77/77 [==============================] - 0s 563us/step - loss: 0.6068 - accuracy: 0.6654 Epoch 39/150 77/77 [==============================] - 0s 512us/step - loss: 0.5952 - accuracy: 0.6849 Epoch 40/150 77/77 [==============================] - 0s 578us/step - loss: 0.5971 - accuracy: 0.6914 Epoch 41/150 77/77 [==============================] - 0s 503us/step - loss: 0.5950 - accuracy: 0.6888 Epoch 42/150 77/77 [==============================] - 0s 530us/step - loss: 0.5968 - accuracy: 0.6797 Epoch 43/150 77/77 [==============================] - 0s 534us/step - loss: 0.6038 - accuracy: 0.6771 Epoch 44/150 77/77 [==============================] - 0s 602us/step - loss: 0.5965 - accuracy: 0.6810 Epoch 45/150 77/77 [==============================] - 0s 625us/step - loss: 0.5972 - accuracy: 0.6667 Epoch 46/150 77/77 [==============================] - 0s 499us/step - loss: 0.5971 - accuracy: 0.6862 Epoch 47/150 77/77 [==============================] - 0s 541us/step - loss: 0.5886 - accuracy: 0.6810 Epoch 48/150 77/77 [==============================] - 0s 503us/step - loss: 0.5946 - accuracy: 0.6810 Epoch 49/150 77/77 [==============================] - 0s 513us/step - loss: 0.5918 - accuracy: 0.6823 Epoch 50/150 77/77 [==============================] - 0s 499us/step - loss: 0.5967 - accuracy: 0.6797 Epoch 51/150 77/77 [==============================] - 0s 547us/step - loss: 0.5931 - accuracy: 0.6836 Epoch 52/150 77/77 [==============================] - 0s 538us/step - loss: 0.5895 - accuracy: 0.6888 Epoch 53/150 77/77 [==============================] - 0s 503us/step - loss: 0.5946 - accuracy: 0.6914 Epoch 54/150 77/77 [==============================] - 0s 535us/step - loss: 0.5865 - accuracy: 0.6901 Epoch 55/150 77/77 [==============================] - 0s 451us/step - loss: 0.5908 - accuracy: 0.6875 Epoch 56/150 77/77 [==============================] - 0s 565us/step - loss: 0.5860 - accuracy: 0.6953 Epoch 57/150 77/77 [==============================] - 0s 459us/step - loss: 0.5850 - accuracy: 0.6953 Epoch 58/150 77/77 [==============================] - 0s 508us/step - loss: 0.5912 - accuracy: 0.6836 Epoch 59/150 77/77 [==============================] - 0s 567us/step - loss: 0.5830 - accuracy: 0.6979 Epoch 60/150 77/77 [==============================] - 0s 643us/step - loss: 0.5936 - accuracy: 0.6914 Epoch 61/150 77/77 [==============================] - 0s 617us/step - loss: 0.5887 - accuracy: 0.6888 Epoch 62/150 77/77 [==============================] - 0s 591us/step - loss: 0.5870 - accuracy: 0.6888 Epoch 63/150 77/77 [==============================] - 0s 564us/step - loss: 0.5773 - accuracy: 0.6992 Epoch 64/150 77/77 [==============================] - 0s 564us/step - loss: 0.5802 - accuracy: 0.6953 Epoch 65/150 77/77 [==============================] - 0s 596us/step - loss: 0.5832 - accuracy: 0.6862 Epoch 66/150 77/77 [==============================] - 0s 577us/step - loss: 0.5843 - accuracy: 0.6927 Epoch 67/150 77/77 [==============================] - 0s 490us/step - loss: 0.5834 - accuracy: 0.6901 Epoch 68/150 77/77 [==============================] - 0s 564us/step - loss: 0.5845 - accuracy: 0.6784 Epoch 69/150 77/77 [==============================] - 0s 611us/step - loss: 0.5894 - accuracy: 0.6875 Epoch 70/150 77/77 [==============================] - 0s 475us/step - loss: 0.5910 - accuracy: 0.6979 Epoch 71/150 77/77 [==============================] - 0s 554us/step - loss: 0.5833 - accuracy: 0.6836 Epoch 72/150 77/77 [==============================] - 0s 539us/step - loss: 0.5825 - accuracy: 0.7005 Epoch 73/150 77/77 [==============================] - 0s 499us/step - loss: 0.5840 - accuracy: 0.6953 Epoch 74/150 77/77 [==============================] - 0s 577us/step - loss: 0.5813 - accuracy: 0.6940 Epoch 75/150 77/77 [==============================] - 0s 590us/step - loss: 0.5747 - accuracy: 0.6914 Epoch 76/150 77/77 [==============================] - 0s 486us/step - loss: 0.5875 - accuracy: 0.6862 Epoch 77/150 77/77 [==============================] - 0s 528us/step - loss: 0.5818 - accuracy: 0.6875 Epoch 78/150 77/77 [==============================] - 0s 564us/step - loss: 0.5893 - accuracy: 0.6849 Epoch 79/150 77/77 [==============================] - 0s 551us/step - loss: 0.5812 - accuracy: 0.6927 Epoch 80/150 77/77 [==============================] - 0s 512us/step - loss: 0.5847 - accuracy: 0.6810 Epoch 81/150 77/77 [==============================] - 0s 577us/step - loss: 0.5828 - accuracy: 0.6953 Epoch 82/150 77/77 [==============================] - 0s 518us/step - loss: 0.5815 - accuracy: 0.6862 Epoch 83/150 77/77 [==============================] - 0s 591us/step - loss: 0.5846 - accuracy: 0.6927 Epoch 84/150 77/77 [==============================] - 0s 591us/step - loss: 0.5925 - accuracy: 0.6901 Epoch 85/150 77/77 [==============================] - 0s 564us/step - loss: 0.5781 - accuracy: 0.6953 Epoch 86/150 77/77 [==============================] - 0s 564us/step - loss: 0.5832 - accuracy: 0.6862 Epoch 87/150 77/77 [==============================] - 0s 512us/step - loss: 0.5801 - accuracy: 0.6979 Epoch 88/150 77/77 [==============================] - 0s 542us/step - loss: 0.5851 - accuracy: 0.6836 Epoch 89/150 77/77 [==============================] - 0s 531us/step - loss: 0.5755 - accuracy: 0.6927 Epoch 90/150 77/77 [==============================] - 0s 564us/step - loss: 0.5749 - accuracy: 0.7005 Epoch 91/150 77/77 [==============================] - 0s 617us/step - loss: 0.5786 - accuracy: 0.6979 Epoch 92/150 77/77 [==============================] - 0s 551us/step - loss: 0.5817 - accuracy: 0.6927 Epoch 93/150 77/77 [==============================] - 0s 564us/step - loss: 0.5834 - accuracy: 0.6927 Epoch 94/150 77/77 [==============================] - 0s 569us/step - loss: 0.5750 - accuracy: 0.6992 Epoch 95/150 77/77 [==============================] - 0s 486us/step - loss: 0.5847 - accuracy: 0.6758 Epoch 96/150 77/77 [==============================] - 0s 538us/step - loss: 0.5781 - accuracy: 0.6927 Epoch 97/150 77/77 [==============================] - 0s 525us/step - loss: 0.5804 - accuracy: 0.6927 Epoch 98/150 77/77 [==============================] - 0s 525us/step - loss: 0.5749 - accuracy: 0.6992 Epoch 99/150 77/77 [==============================] - 0s 590us/step - loss: 0.5779 - accuracy: 0.6927 Epoch 100/150 77/77 [==============================] - 0s 523us/step - loss: 0.5763 - accuracy: 0.6966 Epoch 101/150 77/77 [==============================] - 0s 591us/step - loss: 0.5765 - accuracy: 0.7005 Epoch 102/150 77/77 [==============================] - 0s 499us/step - loss: 0.5816 - accuracy: 0.6966 Epoch 103/150 77/77 [==============================] - 0s 542us/step - loss: 0.5790 - accuracy: 0.6940 Epoch 104/150 77/77 [==============================] - 0s 577us/step - loss: 0.5772 - accuracy: 0.6966 Epoch 105/150 77/77 [==============================] - 0s 591us/step - loss: 0.5778 - accuracy: 0.6966 Epoch 106/150 77/77 [==============================] - 0s 538us/step - loss: 0.5806 - accuracy: 0.6927 Epoch 107/150 77/77 [==============================] - 0s 551us/step - loss: 0.5715 - accuracy: 0.7005 Epoch 108/150 77/77 [==============================] - 0s 486us/step - loss: 0.5808 - accuracy: 0.6914 Epoch 109/150 77/77 [==============================] - 0s 577us/step - loss: 0.5754 - accuracy: 0.6979 Epoch 110/150 77/77 [==============================] - 0s 538us/step - loss: 0.5746 - accuracy: 0.7005 Epoch 111/150 77/77 [==============================] - 0s 569us/step - loss: 0.5778 - accuracy: 0.7018 Epoch 112/150 77/77 [==============================] - 0s 540us/step - loss: 0.5824 - accuracy: 0.6940 Epoch 113/150 77/77 [==============================] - 0s 604us/step - loss: 0.5740 - accuracy: 0.7018 Epoch 114/150 77/77 [==============================] - 0s 512us/step - loss: 0.5755 - accuracy: 0.6966 Epoch 115/150 77/77 [==============================] - 0s 577us/step - loss: 0.5777 - accuracy: 0.6940 Epoch 116/150 77/77 [==============================] - 0s 499us/step - loss: 0.5811 - accuracy: 0.6901 Epoch 117/150 77/77 [==============================] - 0s 538us/step - loss: 0.5780 - accuracy: 0.6992 Epoch 118/150 77/77 [==============================] - 0s 577us/step - loss: 0.5777 - accuracy: 0.6888 Epoch 119/150 77/77 [==============================] - 0s 617us/step - loss: 0.5762 - accuracy: 0.6927 Epoch 120/150 77/77 [==============================] - 0s 565us/step - loss: 0.5716 - accuracy: 0.7031 Epoch 121/150 77/77 [==============================] - 0s 565us/step - loss: 0.5739 - accuracy: 0.7005 Epoch 122/150 77/77 [==============================] - 0s 656us/step - loss: 0.5792 - accuracy: 0.6836 Epoch 123/150 77/77 [==============================] - 0s 604us/step - loss: 0.5813 - accuracy: 0.7005 Epoch 124/150 77/77 [==============================] - 0s 533us/step - loss: 0.5778 - accuracy: 0.6966 Epoch 125/150 77/77 [==============================] - 0s 509us/step - loss: 0.5758 - accuracy: 0.6992 Epoch 126/150 77/77 [==============================] - 0s 525us/step - loss: 0.5722 - accuracy: 0.6914 Epoch 127/150 77/77 [==============================] - 0s 525us/step - loss: 0.5797 - accuracy: 0.6901 Epoch 128/150 77/77 [==============================] - 0s 559us/step - loss: 0.5728 - accuracy: 0.6966 Epoch 129/150 77/77 [==============================] - 0s 559us/step - loss: 0.5726 - accuracy: 0.6992 Epoch 130/150 77/77 [==============================] - 0s 512us/step - loss: 0.5784 - accuracy: 0.6966 Epoch 131/150 77/77 [==============================] - 0s 551us/step - loss: 0.5750 - accuracy: 0.6992 Epoch 132/150 77/77 [==============================] - 0s 525us/step - loss: 0.5745 - accuracy: 0.6992 Epoch 133/150 77/77 [==============================] - 0s 499us/step - loss: 0.5714 - accuracy: 0.6940 Epoch 134/150 77/77 [==============================] - 0s 549us/step - loss: 0.5749 - accuracy: 0.6966 Epoch 135/150 77/77 [==============================] - 0s 501us/step - loss: 0.5780 - accuracy: 0.6992 Epoch 136/150 77/77 [==============================] - 0s 538us/step - loss: 0.5776 - accuracy: 0.7018 Epoch 137/150 77/77 [==============================] - 0s 546us/step - loss: 0.5731 - accuracy: 0.6979 Epoch 138/150 77/77 [==============================] - 0s 577us/step - loss: 0.5720 - accuracy: 0.7031 Epoch 139/150 77/77 [==============================] - 0s 525us/step - loss: 0.5760 - accuracy: 0.6927 Epoch 140/150 77/77 [==============================] - 0s 545us/step - loss: 0.5751 - accuracy: 0.6979 Epoch 141/150 77/77 [==============================] - 0s 551us/step - loss: 0.5738 - accuracy: 0.7057 Epoch 142/150 77/77 [==============================] - 0s 524us/step - loss: 0.5737 - accuracy: 0.7018 Epoch 143/150 77/77 [==============================] - 0s 551us/step - loss: 0.5740 - accuracy: 0.6953 Epoch 144/150 77/77 [==============================] - 0s 514us/step - loss: 0.5751 - accuracy: 0.6940 Epoch 145/150 77/77 [==============================] - 0s 511us/step - loss: 0.5773 - accuracy: 0.6979 Epoch 146/150 77/77 [==============================] - 0s 503us/step - loss: 0.5705 - accuracy: 0.6992 Epoch 147/150 77/77 [==============================] - 0s 494us/step - loss: 0.5738 - accuracy: 0.6979 Epoch 148/150 77/77 [==============================] - 0s 513us/step - loss: 0.5724 - accuracy: 0.6862 Epoch 149/150 77/77 [==============================] - 0s 512us/step - loss: 0.5743 - accuracy: 0.6940 Epoch 150/150 77/77 [==============================] - 0s 480us/step - loss: 0.5691 - accuracy: 0.6979 24/24 [==============================] - 0s 489us/step - loss: 0.5614 - accuracy: 0.7018 准确度 = 0.70
标签：实战,loss,150,0s,程序,step,77,神经网络,accuracy 来源： https://www.cnblogs.com/chinasoft/p/16307734.html