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https://xgboost.readthedocs.io/en/latest/R-package/discoverYourData.html importanceRaw <- xgb.importance(feature_names = sparse_matrix@Dimnames[[2]], model = bst, data = sparse_matrix, label = output_vector)
importanceClean <- importanceRaw[,:=(Cover=NULL, Frequency=NULL)]
:=
head(importanceClean)
our results is : Feature Gain 1: Age 0.60965369 2: TreatmentPlacebo 0.34017103 3: SexMale 0.02340126 4: AgeDiscret6 0.01514658 5: AgeDiscret4 0.01162745
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https://xgboost.readthedocs.io/en/latest/R-package/discoverYourData.html
importanceRaw <- xgb.importance(feature_names = sparse_matrix@Dimnames[[2]], model = bst, data = sparse_matrix, label = output_vector)
Cleaning for better display
importanceClean <- importanceRaw[,
:=
(Cover=NULL, Frequency=NULL)]head(importanceClean)
Feature Split Gain RealCover RealCover %
1: TreatmentPlacebo -1.00136e-05 0.28575061 7 0.2500000
2: Age 61.5 0.16374034 12 0.4285714
3: Age 39 0.08705750 8 0.2857143
4: Age 57.5 0.06947553 11 0.3928571
5: SexMale -1.00136e-05 0.04874405 4 0.1428571
6: Age 53.5 0.04620627 10 0.3571429
our results is : Feature Gain
1: Age 0.60965369
2: TreatmentPlacebo 0.34017103
3: SexMale 0.02340126
4: AgeDiscret6 0.01514658
5: AgeDiscret4 0.01162745
The text was updated successfully, but these errors were encountered: