Closed smarie closed 1 year ago
Linked with #36
This bug arises when some columns in the dataframe are not categorical, and therefore are removed by the model. If the same columnsa re provided later to fit_selector for example, the error is raised
fit_selector
df = pd.DataFrame({ "nb": [1, 2], "name": ["A", "B"] }) qd_forest = qd_screen(df, categorical_mode="convert") feat_selector = qd_forest.fit_selector_model(df) only_important_features_df = feat_selector.remove_qd(df)
A good idea would be to protect our method against invalid inputs (not the expected names or data)
Linked with #36
This bug arises when some columns in the dataframe are not categorical, and therefore are removed by the model. If the same columnsa re provided later to
fit_selector
for example, the error is raisedA good idea would be to protect our method against invalid inputs (not the expected names or data)