h2o.transform-H2OTargetEncoderModel-method: Applies target encoding to a given dataset

In h2o: R Interface for the 'H2O' Scalable Machine Learning Platform

Applies target encoding to a given dataset

Description

Applies target encoding to a given dataset

Usage

## S4 method for signature 'H2OTargetEncoderModel'
h2o.transform(
  model,
  data,
  blending = NULL,
  inflection_point = -1,
  smoothing = -1,
  noise = NULL,
  as_training = FALSE,
  ...
)

Arguments

model	A trained model representing the transformation strategy
data	An H2OFrame with data to be transformed
blending	Use blending during the transformation. Respects model settings when not set.
inflection_point	Blending parameter. Only effective when blending is enabled. By default, model settings are respected, if not overridden by this setting.
smoothing	Blending parameter. Only effective when blending is enabled. By default, model settings are respected, if not overridden by this setting.
noise	An amount of random noise added to the encoding, this helps prevent overfitting. By default, model settings are respected, if not overridden by this setting.
as_training	Must be set to True when encoding the training frame. Defaults to False.
...	Mainly used for backwards compatibility, to allow deprecated parameters.

Value

Returns an H2OFrame object with data transformed.

h2o documentation built on May 29, 2024, 4:26 a.m.