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There appears to be an error with the backward selection algorithm?
While
strategy = Stepwise.first_peak(design,
direction='forward',
max_terms=len(design.terms))
df_Cp = sklearn_selected(OLS,
strategy,
scoring=neg_Cp)
df_Cp.fit(Hitters, Y)
print(df_Cp.selected_state_)
works fine and results in
('Assists', 'AtBat', 'CAtBat', 'CRBI', 'CRuns', 'CWalks', 'Division', 'Hits', 'PutOuts', 'Walks')
If I change the algorithm to 'backward' I get an empty set:
strategy = Stepwise.first_peak(design,
direction='backward',
max_terms=len(design.terms))
df_Cp = sklearn_selected(OLS,
strategy,
scoring=neg_Cp)
df_Cp.fit(Hitters, Y)
print(df_Cp.selected_state_)
results in empty selections
()
()
Since I get similar outcomes with other data sets, I have a suspicion that the 'backward' method is not implemented correctly?
I also noticed that the wrapper does not warn the user when typing a keyword different from 'forward', 'backward' or 'both' and seems to simply revert to 'forward' as the standard method.
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