h2o.coef_norm function

Return coefficients fitted on the standardized data (requires standardize = True, which is on by default). These coefficients can be used to evaluate variable importance.

Return coefficients fitted on the standardized data (requires standardize = True, which is on by default). These coefficients can be used to evaluate variable importance.

h2o.coef_norm(object, predictorSize = -1)

Arguments

  • object: an H2OModel object.
  • predictorSize: predictor subset size. If specified, will only return model coefficients of that subset size. If not specified will return a lists of model coefficient dicts for all predictor subset size.

Examples

## Not run: library(h2o) h2o.init() f <- "https://s3.amazonaws.com/h2o-public-test-data/smalldata/junit/cars_20mpg.csv" cars <- h2o.importFile(f) predictors <- c("displacement", "power", "weight", "acceleration", "year") response <- "cylinders" cars_split <- h2o.splitFrame(data = cars, ratios = 0.8, seed = 1234) train <- cars_split[[1]] valid <- cars_split[[2]] cars_glm <- h2o.glm(balance_classes = TRUE, seed = 1234, x = predictors, y = response, training_frame = train, validation_frame = valid) h2o.coef_norm(cars_glm) ## End(Not run)
  • Maintainer: Tomas Fryda
  • License: Apache License (== 2.0)
  • Last published: 2024-01-11