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It can be done by passing an extra X to the fit function, for example, like this:
X=df.loc[:, df.columns != "event_value"]
Here, I'm assuming the external regressors are given as additional columns in the BeliefsDataFrame. They need to be passed through correctly, though. And also tested properly. NB Testing it with sktime's naive forecaster will just lead to the forecaster ignoring X.
The X above is already added in PR #50. A little comment would help. Also add an optional parameter to form_beliefs, e.g. "X_column_names", and check for cases where columns in X would be bad to include.
The text was updated successfully, but these errors were encountered:
Originally posted by @Flix6x in #50 (comment):
It can be done by passing an extra
X
to the fit function, for example, like this:Here, I'm assuming the external regressors are given as additional columns in the BeliefsDataFrame. They need to be passed through correctly, though. And also tested properly. NB Testing it with sktime's naive forecaster will just lead to the forecaster ignoring
X
.Originally posted by @nhoening in #50 (comment):
The
X
above is already added in PR #50. A little comment would help. Also add an optional parameter toform_beliefs
, e.g. "X_column_names", and check for cases where columns in X would be bad to include.The text was updated successfully, but these errors were encountered: