我有多个串联的时间序列,我想用它们来训练我的LSTM模型。我想避免一个时间序列的预测是基于另一个时间序列的特征的。因此,我尝试在循环中使用TimeseriesGenerator。我的代码看起来像这样
def data_generator(X, y, batch_size, look_back):
generators = []
for train_session in np.unique(X[:, -1]):
mask = X[:, -1] == train_session
X = X[mask]
y = y[mask]
generators.append(TimeseriesGenerator(X,
y,
length=look_back,
batch_size=batch_size))
yield next(generators)
运行model.fit_generator时出现以下错误:
ValueError: `start_index+length=10 > end_index=-1` is disallowed, as no part of the sequence would be left to be used as current step.
这是什么问题,我该如何解决?
谢谢