select_models: select_models

In andrewsommerlot/startml: Start doing machine learning with training optimization and ensembles of popular machine learning algorithms powered by scalable implementations in h2o

Description

select_models identifies best models in mlblob object by performance and pearson correlation thresholds.

Usage

select_models(model_list, test, eval_metric, y, eval_threshold = NULL,
  correlation_threshold = NULL)

Arguments

model_list	List object of H2O model objects to be subbsetted by performance and correlation thresholds No Default.
test	H2O frame object containing labeled data for model evaluation. No Default.
eval_metric	Character object one of logloss, MSE, RMSE, MAE, AUC, or mean_per_class_error.
y	Character object of length 1 identifying the column name of the target variable. No Default.
eval_threshold	Numeric object defining the performance threshold models must meet to be used in prediction. Is minimum for maximization loss function (i.e., AUC) and maximum for minimization loss functions (logloss, MSE, etc). Default is NULL, returns models without performance consideration.
correlation_threshold	Numeric object defining the maximum person correlation allowed in the group of resulting models. If two models show high correlation, the one with surperior performance will be kept and the other dropped. Value ranges from -1 to 1, default is NULL, returning models without correlation considered.

Value

List object containing H2O model objects adhearing to threshold standards set in input arguments.

andrewsommerlot/startml documentation built on May 5, 2019, 6:58 p.m.