v0.16.8

EvoTrees v0.16.8

Diff since v0.16.7

Merged pull requests:

• up (#271) (@jeremiedb)
• adhere to MLJ interface (#272) (@OkonSamuel)

v0.16.7

EvoTrees v0.16.7

Diff since v0.16.6

Merged pull requests:

• Issue/267 (#268) (@jeremiedb)

Closed issues:

• Feature Request: piecewise linear gradient boosting tree (#241)
• Citation (#265)
• In MLJ interface, classifier makes unordered class predictions for ordered training target (#267)

v0.16.6

EvoTrees v0.16.6

Diff since v0.16.5

Merged pull requests:

• DOI (#266) (@jeremiedb)

v0.16.5

EvoTrees v0.16.5

Diff since v0.16.4

Merged pull requests:

• Mlj table (#262) (@jeremiedb)
• CompatHelper: add new compat entry for Statistics at version 1, (keep existing compat) (#263) (@github-actions[bot])
• L2 (#264) (@jeremiedb)

Closed issues:

• EvoTrees consumes too much memory and crashes for sparse matrices (#87)
• Categorical Variables Not Working (#260)

v0.16.4

EvoTrees v0.16.4

Diff since v0.16.3

Merged pull requests:

• Debug gpu (#261) (@jeremiedb)

v0.16.3

EvoTrees v0.16.3

Diff since v0.16.2

Merged pull requests:

• Create CUDA extension (#259) (@devmotion)

Closed issues:

• Make CUDA a weak dependency (#226)
• Document how missing values should be handled by user (#247)

v0.16.2

EvoTrees v0.16.2

Diff since v0.16.1

Merged pull requests:

• Ranking tutorial (#254) (@jeremiedb)
• CompatHelper: bump compat for "CUDA" to "5.0" (#255) (@github-actions[bot])
• Missings (#258) (@jeremiedb)

Closed issues:

• Initialization of rng (#245)
• Shuffling feature order when changing seed (#246)
• Can't find plot function (#253)
• Example for how to use EvoTrees.jl as a component of a more complicated model (#256)

v0.16.1

EvoTrees v0.16.1

Diff since v0.16.0

Merged pull requests:

• Stochastic (#252) (@jeremiedb)

v0.16.0

EvoTrees v0.16.0

Diff since v0.15.2

Closed issues:

• Threading issue (#248)

Merged pull requests:

• Threading (#249) (@jeremiedb)
• Shuffling (#250) (@jeremiedb)

v0.15.2

EvoTrees v0.15.2

Diff since v0.15.1

Merged pull requests:

• Perf depth (#244) (@jeremiedb)