TF之LSTM:基于tensorflow框架自定义LSTM算法实现股票历史(1990~2015数据集,6112预测后100+单变量最高)行情回归预测

TF之LSTM:基于tensorflow框架自定义LSTM算法实现股票历史(1990~2015数据集,6112预测后100+单变量最高)行情回归预测


输出结果

数据集

LSTM代码

def LSTM(batch):
    w_in=weights['in']
    b_in=biases['in']
    input_rnn=tf.matmul(input,w_in)+b_in
    input_rnn=tf.reshape(input_rnn,[-1,time_step,rnn_unit])
    cell=tf.nn.rnn_cell.BasicLSTMCell(rnn_unit)
    init_state=cell.zero_state(batch,dtype=tf.float32)
    output_rnn,final_states=tf.nn.dynamic_rnn(cell, input_rnn,initial_state=init_state, dtype=tf.float32)
    output=tf.reshape(output_rnn,[-1,rnn_unit])
    w_out=weights['out']
    b_out=biases['out']
    pred=tf.matmul(output,w_out)+b_out
    return pred,final_states
 
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