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h2o.computeGram

Compute weighted gram matrix.


Description

Compute weighted gram matrix.

Usage

h2o.computeGram(
  X,
  weights = "",
  use_all_factor_levels = FALSE,
  standardize = TRUE,
  skip_missing = FALSE
)

Arguments

X

an H2OModel corresponding to H2O framel.

weights

character corresponding to name of weight vector in frame.

use_all_factor_levels

logical flag telling h2o whether or not to skip first level of categorical variables during one-hot encoding.

standardize

logical flag telling h2o whether or not to standardize data

skip_missing

logical flag telling h2o whether skip rows with missing data or impute them with mean


h2o

R Interface for the 'H2O' Scalable Machine Learning Platform

v3.32.1.2
Apache License (== 2.0)
Authors
Erin LeDell [aut, cre], Navdeep Gill [aut], Spencer Aiello [aut], Anqi Fu [aut], Arno Candel [aut], Cliff Click [aut], Tom Kraljevic [aut], Tomas Nykodym [aut], Patrick Aboyoun [aut], Michal Kurka [aut], Michal Malohlava [aut], Ludi Rehak [ctb], Eric Eckstrand [ctb], Brandon Hill [ctb], Sebastian Vidrio [ctb], Surekha Jadhawani [ctb], Amy Wang [ctb], Raymond Peck [ctb], Wendy Wong [ctb], Jan Gorecki [ctb], Matt Dowle [ctb], Yuan Tang [ctb], Lauren DiPerna [ctb], Tomas Fryda [ctb], H2O.ai [cph, fnd]
Initial release
2021-04-29

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