iter_seeds: Iterate Seeds on AutoML

In lares: Analytics & Machine Learning Sidekick

Iterate Seeds on AutoML

Description

This functions lets the user iterate and search for best seed. Note that if the results change a lot, you are having a high variance in your data.

Usage

iter_seeds(df, y, tries = 10, ...)

Arguments

df	Dataframe. Dataframe containing all your data, including the dependent variable labeled as 'tag'. If you want to define which variable should be used instead, use the y parameter.
y	Variable or Character. Name of the dependent variable or response.
tries	Integer. Number of iterations
...	Additional arguments passed to h2o_automl

Value

data.frame with performance results by seed tried on every row.

See Also

Other Machine Learning: ROC(), conf_mat(), export_results(), gain_lift(), h2o_automl(), h2o_predict_MOJO(), h2o_selectmodel(), impute(), lasso_vars(), model_metrics(), model_preprocess(), msplit()

lares documentation built on Sept. 13, 2024, 1:08 a.m.