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Releases: CIRL-UNC/SuperLearnerMacro

v1.1.1

19 Sep 16:16
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Bug fix release

Fixed a critical bug that prevented many of the B-methods from converging in small datasets.

v1.1

19 Sep 02:34
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Includes new/improved learners

  • highly adaptive lasso (hal, ahal, ahalb)
  • lasso with cross validation (cvlasso)

Features

  • Cross validation now respects clustering/individuals with multiple records via "id" macro variable - this allows for survival analysis via discrete hazard functions! The SuperLearner macro now implements every primary feature of the R super learner package.

Bug fixes

  • major: hard coded outcome variable names in some learners
  • minor: improved macro variable scoping, which may have caused some errors in limited circumstances

Aesthetics

  • improved responsiveness of output

v1.0

19 Jul 04:03
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Official stable release in preparation for manuscript

Beta 2

26 May 16:41
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Beta 2 Pre-release
Pre-release

Multiple bug fixes including full implementation of seed values, fixed ridge regression, several R learners

Features: added Ridge regression to estimate super learner fit, harmonized adaptive random forest super learner with other methods to give identical output

Beta release

23 May 15:19
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Beta release Pre-release
Pre-release

Pre-release of version 1.0