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Some support for regression models is there, but it needs to be tested! Also, h2o.varimp() output is model specific!
h2o.varimp()
The text was updated successfully, but these errors were encountered:
Here is what h2o is doing internally (will need to check for NULL):
h2o
NULL
#' #' Retrieve the variable importance. #' #' @param object An \linkS4class{H2OModel} object. #' @export h2o.varimp <- function(object) { o <- object if( is(o, "H2OModel") ) { vi <- o@model$variable_importances if( is.null(vi) ) { vi <- object@model$standardized_coefficient_magnitudes } # no true variable importances, maybe glm coeffs? (return standardized table...) if( is.null(vi) ) { warning("This model doesn't have variable importances", call. = FALSE) return(invisible(NULL)) } vi } else { warning( paste0("No variable importances for ", class(o)) ) return(NULL) } }
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Some support for regression models is there, but it needs to be tested! Also,
h2o.varimp()
output is model specific!The text was updated successfully, but these errors were encountered: