RemixAutoML (version 0.2.8)

RemixClassificationMetrics: RemixClassificationMetrics

Description

RemixClassificationMetrics

Usage

RemixClassificationMetrics(
  MLModels = c("catboost", "h2oautoml", "h2ogbm", "h2odrf", "xgboost"),
  TargetVariable = "Value",
  Thresholds = seq(0.01, 0.99, 0.01),
  CostMatrix = c(1, 0, 0, 1),
  ClassLabels = c(1, 0),
  CatBoostTestData = NULL,
  H2oAutoMLTestData = NULL,
  H2oGBMTestData = NULL,
  H2oDRFTestData = NULL,
  H2oGLMTestData = NULL,
  XGBoostTestData = NULL
)

Arguments

MLModels

A vector of model names from remixautoml. e.g. c("catboost","h2oautoml","h2ogbm","h2odrf","h2oglm","xgboost")

TargetVariable

Name of your target variable

Thresholds

seq(0.01,0.99,0.01),

CostMatrix

c(1,0,0,1),

ClassLabels

c(1,0),

CatBoostTestData

Test data returned from AutoCatBoostClassifier

H2oAutoMLTestData

Test data returned from AutoCatBoostClassifier

H2oGBMTestData

Test data returned from AutoH2oGBMClassifier

H2oDRFTestData

Test data returned from AutoH2oDRFClassifier

H2oGLMTestData

Test data returned from AutoH2oGLMClassifier

XGBoostTestData

Test data returned from AutoXGBoostClassifier

See Also

Other Model Evaluation: ClassificationMetrics(), DT_BinaryConfusionMatrix()

Examples

# NOT RUN {
RemixClassificationMetrics <- function(
  MLModels = c("catboost",
               "h2oautoml",
               "h2ogbm",
               "h2odrf",
               "xgboost"),
  TargetVariable = "Value",
  Thresholds = seq(0.01,0.99,0.01),
  CostMatrix = c(1,0,0,1),
  ClassLabels = c(1,0),
  CatBoostTestData = NULL,
  H2oAutoMLTestData = NULL,
  H2oGBMTestData = NULL,
  H2oDRFTestData = NULL,
  H2oGLMTestData = NULL,
  XGBoostTestData = NULL)
# }