lstm模型二分类代码

以下是一个使用LSTM模型进行二分类的示例代码：

import numpy as np
import tensorflow as tf

# 加载数据
X_train = ... # shape: (num_samples, sequence_length, input_dim)
y_train = ... # shape: (num_samples, 1)

# 创建LSTM模型
model = tf.keras.Sequential([
    tf.keras.layers.LSTM(units=64, input_shape=(X_train.shape[1], X_train.shape[2])),
    tf.keras.layers.Dense(units=1, activation='sigmoid')
])

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

# 训练模型
model.fit(X_train, y_train, epochs=10, batch_size=32)

# 预测新数据
X_test = ... # shape: (num_samples, sequence_length, input_dim)
y_pred = model.predict(X_test)

# 将预测结果转换为二分类结果
y_pred_binary = np.round(y_pred).astype(int)