v0.10.1

BetaML v0.10.1

Diff since v0.10.0

Closed issues:

• target_scitype for MultitargetNeuralNetworkRegressor is too broad (#53)

Merged pull requests:

• CompatHelper: bump compat for StatsBase to 0.34, (keep existing compat) (#54) (@github-actions[bot])

v0.10.0

BetaML v0.10.0

Diff since v0.9.7

v0.9.7

BetaML v0.9.7

Diff since v0.9.6

Closed issues:

• Trouble interpolating feature names in a wrapped tree (#48)
• MLJ model docstrings (#49)
• GaussianMixtureModelClusterer docstring has formatting issues (#50)

v0.9.6

BetaML v0.9.6

Diff since v0.9.5

Merged pull requests:

• add test for plotting a tree using TreeRecipe (#47) (@roland-KA)

v0.9.5

BetaML v0.9.5

Diff since v0.9.4

• new function match_known_derivatives to set corresponding manual derivatives for well known activation or loss functions in NN and its implementation as default of the derivatives instead of nothing (i.e. AD)
• new ConvLayer and PoolLayer. while very flexible (any dimension, any function) they are way too slow for any practical work, even if the convolution ids are cached. A pitty!

v0.9.4

BetaML v0.9.4

Diff since v0.9.3

• examples on all v2 API models

Closed issues:

• Add MLJ-compliant document strings (#39)

v0.9.3

BetaML v0.9.3

Diff since v0.9.2

• examples in doc (expecially MLJ interface), minor bugfixes

v0.9.2

BetaML v0.9.2

Diff since v0.9.1

• removed a warning that slipped in v0.9.1

v0.9.1

BetaML v0.9.1

Diff since v0.9.0

• cleaned up "old" deprecated v1 api
• started implementation (forward pass) of a generic n-dimensional ConvLayer
• printing of Decision Trees (@roland-KA )
• improved documentation
• new dependency on StaticArrays
• changed verbosity in MLJ models

Closed issues:

• Example with GaussianMixtureClusterer (#43)
• Allow verbosity to be any integer? (#44)

Merged pull requests:

• CompatHelper: add new compat entry for StaticArrays at version 1, (keep existing compat) (#45) (@github-actions[bot])
• Adapt to new AbstractTrees.AbstractNode type (#46) (@roland-KA)

v0.9.0

BetaML v0.9.0

Diff since v0.8.0

• clean up of old functions deemed deprecated: either removed the code or unexported in favour of API v2
• added some optimisations and support for LoopVectorization
• renamed shuffle to consistent_shuffle to avoid type piracy
• completed documentation of MLJ models

Closed issues:

• Error during precompilation (ERROR: LoadError: InitError: Evaluation into the closed module Perceptron ...) (#42)

Merged pull requests:

• JuliaCall from PythonCall.jl (#41) (@PallHaraldsson)