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5.2.1

Selection of Training Populations by Genetic Algorithm

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Overview

About
Maintained by Deniz AkdemirFirst published 2014-05-318 releasesCRAN page ↗

Combining Predictive Analytics and Experimental Design to Optimize Results. To be utilized to select a test data calibrated training population in high dimensional prediction problems and assumes that the explanatory variables are observed for all of the individuals. Once a "good" training set is identified, the response variable can be obtained only for this set to build a model for predicting the response in the test set. The algorithms in the package can be tweaked to solve some other subset selection problems.

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Slowest check: 1.3 min · r-oldrel-windows-x86_64
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Tests · ratio 0.00
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Check history
  • NOTE2026-03-10
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Documentation

Documentation
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Examples that run
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Documented parameters
97%
Return-value docs
100%
References docs
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Dependencies

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10 external dependencies (excludes base and recommended)
Depends (6)
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Listed in earlier versions (1)
no longer listed · 1.0 to 5.2.1
Package Timeline

8 releases. Pick two to compare their code metrics. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
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    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • R
    R 4.3.0 released · 2023-04-21
  • R
    R 4.2.0 released · 2022-04-22
  • R
    R 4.1.0 released · 2021-05-18
  • R
    R 4.0.0 released · 2020-04-24
  • R
    R 3.6.0 released · 2019-04-26
  • 5.2.1Latest
    2018-11-24 · current release · diff ↗
  • 5.2
    2018-09-21 · diff ↗
  • 5.1
    2018-08-16 · diff ↗
  • 5.0
    2018-07-22 · diff ↗
  • R
    R 3.5.0 released · 2018-04-23
  • R
    R 3.4.0 released · 2017-04-21
  • 4.0
    2017-03-02 · diff ↗
  • 3.0
    2016-08-09 · diff ↗
Show 5 earlier events
  • 2.0
    2016-05-05 · diff ↗
  • R
    R 3.3.0 released · 2016-05-03
  • R
    R 3.2.0 released · 2015-04-16
  • 1.0
    2014-05-31
  • R
    R 3.1.0 released · 2014-04-10

Package metadata

First published
2014-05-31
Total releases
8 / 12 yrs
License
GPL-3 OSI
Minimum R
≥ 2.10
Bundled data
390 KB / 1 file
Download size
409 KB
Installed size
not tracked yet
With dependencies
not tracked yet
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