FeaLect

Scores Features for Feature Selection

For each feature, a score is computed that can be useful for feature selection. Several random subsets are sampled from the input data and for each random subset, various linear models are fitted using lars method. A score is assigned to each feature based on the tendency of LASSO in including that feature in the models.Finally, the average score and the models are returned as the output. The features with relatively low scores are recommended to be ignored because they can lead to overfitting of the model to the training data. Moreover, for each random subset, the best set of features in terms of global error is returned. They are useful for applying Bolasso, the alternative feature selection method that recommends the intersection of features subsets.

Total

15,830

Last month

285

Last week

35

Average per day

10

Daily downloads

Total downloads

Description file content

Package
FeaLect
Type
Package
Title
Scores Features for Feature Selection
Version
1.14
Date
2018-05-31
Author
Habil Zare
Maintainer
Habil Zare
Depends
lars, rms
Description
For each feature, a score is computed that can be useful for feature selection. Several random subsets are sampled from the input data and for each random subset, various linear models are fitted using lars method. A score is assigned to each feature based on the tendency of LASSO in including that feature in the models.Finally, the average score and the models are returned as the output. The features with relatively low scores are recommended to be ignored because they can lead to overfitting of the model to the training data. Moreover, for each random subset, the best set of features in terms of global error is returned. They are useful for applying Bolasso, the alternative feature selection method that recommends the intersection of features subsets.
License
GPL (>= 2)
LazyLoad
yes
Repository
CRAN
Date/Publication
2018-06-01 13:13:46 UTC
Packaged
2018-06-01 00:07:37 UTC; habil
NeedsCompilation
no
RoxygenNote
6.0.1

install.packages('FeaLect')

1.14

a month ago

Habil Zare

GPL (>= 2)

Depends on

lars, rms

Discussions