如下所示验证测试数据上的模型,然后绘制准确度和损失
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy']) history = model.fit(X_train, y_train, nb_epoch=10, validation_data=(X_test, y_test), shuffle=True)
它是相同的,因为你在测试集上训练,而不是在火车上训练。不要这样做,只需训练训练集:
history = model.fit(x_test, y_test, nb_epoch=10, validation_split=0.2, shuffle=True)
变成:
history = model.fit(x_train, y_train, nb_epoch=10, validation_split=0.2, shuffle=True)