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Home Page: https://sintel.dev/ml-stars/
License: MIT License
Primitives and Pipelines for Time Series Data
Home Page: https://sintel.dev/ml-stars/
License: MIT License
I am trying to create rolling window sequences to feed as input to a reconstruction model (LSTM-AE). Since it's not prediction, you want target_size = 0 so that the last window contains the last point, i.e. all points are captured in the window sequences. However, setting target_size = 0 raises an indexing error at line 108 aka
y_index.append(index[end + offset])
in mlstars/custom/timeseries_preprocessing.py
.
sample = 'E-10'
train_data = load_signal('multivariate/' + sample)
train_data.head()
window = 100
primitive = load_primitive('mlstars.custom.timeseries_preprocessing.rolling_window_sequences',
arguments = {
'index': train_data.index,
'window_size': window,
'target_size': 0,
'step_size': 1,
'target_column': None
})
X, y, index, target_index = primitive.produce(X=train_data.drop('timestamp', axis=1).to_numpy())
ubuntu
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