R/glm.R
Compute weighted gram matrix.
h2o.computeGram(X, weights = "", use_all_factor_levels = FALSE, standardize = TRUE, skip_missing = FALSE)
| 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 |