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RemixAutoML (version 0.5.0)

ML_EvalPlots: ML_EvalPlots

Description

Generate evaluation plots

Usage

ML_EvalPlots(
  ModelType = "classification",
  TrainOnFull. = TrainOnFull,
  LossFunction. = LossFunction,
  EvalMetric. = EvalMetric,
  EvaluationMetrics. = EvaluationMetrics,
  ValidationData. = ValidationData,
  NumOfParDepPlots. = NumOfParDepPlots,
  VariableImportance. = VariableImportance,
  TargetColumnName. = TargetColumnName,
  FeatureColNames. = FeatureColNames,
  SaveModelObjects. = SaveModelObjects,
  ModelID. = ModelID,
  metadata_path. = metadata_path,
  model_path. = model_path,
  predict. = predict
)

Arguments

ModelType

'classification', 'multiclass', 'regression', or 'vector'

TrainOnFull.

Passthrough

LossFunction.

Passthrough regression

EvalMetric.

Passthrough regression

EvaluationMetrics.

Passthrough regression

ValidationData.

Passthrough

NumOfParDepPlots.

Passthrough

VariableImportance.

Passthrough

TargetColumnName.

Passthrough

FeatureColNames.

Passthrough

SaveModelObjects.

Passthrough

ModelID.

Passthrough

metadata_path.

Passthrough

model_path.

Passthrough

See Also

Other Model Evaluation and Interpretation: AutoLimeAid(), EvalPlot(), LimeModel(), ParDepCalPlots(), ROCPlot(), RedYellowGreen(), VI_Plot(), threshOptim()