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h2o (version 3.16.0.2)

h2o.aggregator: Builds an Aggregated Frame of an H2OFrame

Description

Builds an Aggregated Frame of an H2OFrame

Usage

h2o.aggregator(training_frame, x, model_id = NULL, ignore_const_cols = TRUE,
  target_num_exemplars = 5000, rel_tol_num_exemplars = 0.5,
  transform = c("NONE", "STANDARDIZE", "NORMALIZE", "DEMEAN", "DESCALE"),
  categorical_encoding = c("AUTO", "Enum", "OneHotInternal", "OneHotExplicit",
  "Binary", "Eigen", "LabelEncoder", "SortByResponse", "EnumLimited"))

Arguments

training_frame

Id of the training data frame.

x

A vector containing the character names of the predictors in the model.

model_id

Destination id for this model; auto-generated if not specified.

ignore_const_cols

Logical. Ignore constant columns. Defaults to TRUE.

target_num_exemplars

Targeted number of exemplars Defaults to 5000.

rel_tol_num_exemplars

Relative tolerance for number of exemplars (e.g, 0.5 is +/- 50 percents) Defaults to 0.5.

transform

Transformation of training data Must be one of: "NONE", "STANDARDIZE", "NORMALIZE", "DEMEAN", "DESCALE". Defaults to NORMALIZE.

categorical_encoding

Encoding scheme for categorical features Must be one of: "AUTO", "Enum", "OneHotInternal", "OneHotExplicit", "Binary", "Eigen", "LabelEncoder", "SortByResponse", "EnumLimited". Defaults to AUTO.