Question

我正在尝试训练神经网络，我想知道当我调用函数validate时如何检索由神经网络计算的标签值。

我在keras文档中搜索了一个做到这一点的参数，但我什么都没找到。

import tensorflow as tf
from tensorflow import keras
import numpy as np

# Create the array of data

train_data = [[1.0,2.0,3.0],[4.0,5.0,6.0]]
train_data_np = np.asarray(train_data)
train_label = [[1,2,3],[4,5,6]]
train_label_np = np.asarray(train_data)

### Build the model

model = keras.Sequential([
    keras.layers.Dense(3,input_shape =(3,2)),
    keras.layers.Dense(3,activation=tf.nn.sigmoid)
])

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

#Train the model

model.fit(train_data_np,train_label_np,epochs=10)

#test the model
restest = model.evaluate(test_data_np,test_label_np)

Answer 1

在评估模型之前，您应该预测测试集的标签：

#predicting 
predict_labels = model.predict(test_data_np)
#evaluate
restest = model.evaluate(test_label_np,predict_labels)

获取测试对象（模型。评估）神经网络的值标签

1 个答案: