`R/models.R`

`h2o.coef_norm.Rd`

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)

object | an H2OModel object. |
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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. |

if (FALSE) { 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) }