Package: FSelector 0.34
FSelector: Selecting Attributes
Functions for selecting attributes from a given dataset. Attribute subset selection is the process of identifying and removing as much of the irrelevant and redundant information as possible.
Authors:
FSelector_0.34.tar.gz
FSelector_0.34.zip(r-4.5)FSelector_0.34.zip(r-4.4)FSelector_0.34.zip(r-4.3)
FSelector_0.34.tgz(r-4.4-any)FSelector_0.34.tgz(r-4.3-any)
FSelector_0.34.tar.gz(r-4.5-noble)FSelector_0.34.tar.gz(r-4.4-noble)
FSelector_0.34.tgz(r-4.4-emscripten)FSelector_0.34.tgz(r-4.3-emscripten)
FSelector.pdf |FSelector.html✨
FSelector/json (API)
# Install 'FSelector' in R: |
install.packages('FSelector', repos = c('https://larskotthoff.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/larskotthoff/fselector/issues
Last updated 1 years agofrom:26c313ca5e. Checks:OK: 3 NOTE: 4. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 15 2024 |
R-4.5-win | NOTE | Oct 15 2024 |
R-4.5-linux | NOTE | Oct 15 2024 |
R-4.4-win | NOTE | Oct 15 2024 |
R-4.4-mac | NOTE | Oct 15 2024 |
R-4.3-win | OK | Oct 15 2024 |
R-4.3-mac | OK | Oct 15 2024 |
Exports:as.simple.formulabackward.searchbest.first.searchcfschi.squaredconsistencycutoff.biggest.diffcutoff.kcutoff.k.percentexhaustive.searchforward.searchgain.ratiohill.climbing.searchinformation.gainlinear.correlationoneRrandom.forest.importancerank.correlationreliefsymmetrical.uncertainty
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Package for selecting attributes | FSelector-package FSelector |
Converting to formulas | as.simple.formula |
Best-first search | best.first.search |
CFS filter | cfs |
Chi-squared filter | chi.squared |
Consistency-based filter | consistency |
Correlation filter | linear.correlation rank.correlation |
Cutoffs | cutoff.biggest.diff cutoff.k cutoff.k.percent |
Entropy-based filters | gain.ratio information.gain symmetrical.uncertainty |
Exhaustive search | exhaustive.search |
Greedy search | backward.search forward.search |
Hill climbing search | hill.climbing.search |
OneR algorithm | oneR |
RandomForest filter | random.forest.importance |
RReliefF filter | relief |