验证损失低于训练损失，并在Keras中减少损失

import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout
from tensorflow.keras.callbacks import EarlyStopping

# 创建一个简单的模型
model = Sequential([
    Dense(64, activation='relu', input_shape=(input_dim,)),
    Dropout(0.5),
    Dense(32, activation='relu'),
    Dropout(0.5),
    Dense(1, activation='sigmoid')
])

# 编译模型
model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])

# 设置早停法回调
early_stopping = EarlyStopping(monitor='val_loss', patience=3)

# 训练模型
history = model.fit(
    x_train, y_train,
    validation_data=(x_val, y_val),
    epochs=100,
    batch_size=32,
    callbacks=[early_stating]
)