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Hi, I am trying to send a custom sklearn compatible CV splitter and it appears that the code in PyImpetus is just defaulting to KFold:
# for a value of 0, no CV is applied
if self.cv!= 0:
...
else:
kfold = KFold(n_splits=self.cv, random_state=self.random_state, shuffle=True)
if self.verbose > 0:
with tqdm_joblib(tqdm(desc="Progress bar", total=self.cv)) as progress_bar:
tmp = parallel(delayed(self._find_MB)(data.iloc[train].copy(), Y[train]) for train, test in kfold.split(data))
else:
tmp = parallel(delayed(self._find_MB)(data.iloc[train].copy(), Y[train]) for train, test in kfold.split(data))
Instead, I was expecting PyImpetus should just use the cv splitter from cv argument:
# for a value of 0, no CV is applied
if self.cv!= 0:
...
else:
if self.verbose > 0:
with tqdm_joblib(tqdm(desc="Progress bar", total=self.cv)) as progress_bar:
tmp = parallel(delayed(self._find_MB)(data.iloc[train].copy(), Y[train]) for train, test in self.cv.split(data))
else:
tmp = parallel(delayed(self._find_MB)(data.iloc[train].copy(), Y[train]) for train, test in self.cv.split(data))
The text was updated successfully, but these errors were encountered:
Hi, I am trying to send a custom sklearn compatible CV splitter and it appears that the code in PyImpetus is just defaulting to KFold:
Instead, I was expecting PyImpetus should just use the cv splitter from cv argument:
The text was updated successfully, but these errors were encountered: