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MachineShop 3.3.0
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@brian-j-smith brian-j-smith released this 09 Feb 13:46
· 113 commits to master since this release
v3.3.0
3260315

Version Updates

3.3.0

  • Add argument .type with options "glance" and "tidy" to summary.MLModelFit().
  • Add case components data (stratification and grouping variables) to print.Resample().
  • Add class and methods for ModelSpecification.
  • Add training parameters set functions
    • set_monitor(): monitoring of resampling and optimization
    • set_optim_bayes(): Bayesian optimization with a Gaussian process model
    • set_optim_bfgs(): low-memory quasi-Newton BFGS optimization
    • set_optim_grid(): exhaustive and random grid searches
    • set_optim_method(): user-defined optimization functions
    • set_optim_pso(): particle swarm optimization
    • set_optim_sann(): simulated annealing
  • Add performance() method for MLModel to replicate the previous behavior of summary.MLModel().
  • Add performance(), plot(), and summary() methods for TrainingStep.
  • Add support for unordered plots of Resample performances.
  • Changes to argument type of predict().
    • Add option "default" for model-specific default predictions.
    • Add option "numeric" for numeric predictions.
    • Change option "prob" to be for probabilities between 0 and 1.
  • Change confusion() default behavior to convert factor probabilities to levels.
  • Rename argument control to object in set functions.
  • Rename argument f to fun in roc_index().
  • Return a ListOf training step summaries from summary.MLModel().
  • Return a TrainingStep object from rfe().
  • Support tibble-convertible objects as arguments to expand_params().
  • Internal changes
    • Add class EnsembleModel.
    • Add classes MLOptimization, GridSearch, NullOptimization, RandomGridSearch, and SequentialOptimization.
    • Add class NullControl.
    • Add slot control to PerformanceCurve.
    • Add slot method to TrainingStep.
    • Add slot optim to TrainingParams.
    • Add slot params to MLInput.
    • Inherit class SelectedModel from EnsembleModel.
    • Inherit class StackedModel from EnsembleModel.
    • Inherit class SuperModel from StackedModel.
    • Rename slot case_comps to vars in Resample.
    • Rename slot grid to log in TrainingStep.
  • Fixes
    • error predicting single factor response in GLMModel
    • 'size(x@performance, 3)' error in print.TrainingStep()
    • 'Unmatched tuning parameters' error in TunedModel()

3.2.1

  • Fix 'data' argument of wrong type error in terms.formula().
  • Require >= 3.1.0 version of cli package.
Assets 2
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