h2o.svd(training_frame, x, destination_key, model_id = NULL, validation_frame = NULL, ignore_const_cols = TRUE, score_each_iteration = FALSE, transform = c("NONE", "STANDARDIZE", "NORMALIZE", "DEMEAN", "DESCALE"), svd_method = c("GramSVD", "Power", "Randomized"), nv = 1, max_iterations = 1000, seed = -1, keep_u = TRUE, u_name = NULL, use_all_factor_levels = TRUE, max_runtime_secs = 0)
character
names of the predictors in the model.Logical
. Ignore constant columns. Defaults to TRUE.Logical
. Whether to score during each iteration of model training. Defaults to FALSE.Logical
. Save left singular vectors? Defaults to TRUE.Logical
. Whether first factor level is included in each categorical expansion Defaults to TRUE.
library(h2o)
h2o.init()
ausPath <- system.file("extdata", "australia.csv", package="h2o")
australia.hex <- h2o.uploadFile(path = ausPath)
h2o.svd(training_frame = australia.hex, nv = 8)
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