Pradeep Reddy Raamana
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Pradeep Reddy Raamana
``` xgboost.core.XGBoostError: b"Invalid Parameter format for num_feature expect int (non-negative) but value='sqrt'" ``` It seems like XGBoost does not accept num_feature parameter anymore - their docs say "it does not...
Atleast parameters most often selected
Missing functionality: non-parametric friedman test on the results from RHsT
Ensure all parameters are estimated only from training data in sklearn
Separate file at the top level, one line with a label per feature
Groups of features not significantly different from each other! Focus on intuitive interpretability, even if it means generating more than one figure.
nemenyi posthoc analysis
perhaps ds.target_name(s) feature ?