This function calculates cumulative gain, lift, and response values for a predictive score of a specific target. You can use the mplot_gain() function to custom plot results.
gain_lift(tag, score, target = "auto", splits = 10, plot = FALSE,
quiet = FALSE)Vector. Real known label
Vector. Predicted value or model's result
Value. Which is your target positive value? If set to 'auto', the target with largest mean(score) will be selected. Change the value to overwrite.
Integer. Numer of percentiles to split the data
Boolean. Plot results?
Boolean. Do not show message for auto target?
Other Machine Learning: ROC,
clusterKmeans, conf_mat,
export_results, h2o_automl,
h2o_predict_API,
h2o_predict_MOJO,
h2o_predict_binary,
h2o_predict_model,
h2o_selectmodel, impute,
iter_seeds, model_metrics,
mplot_conf, mplot_cuts_error,
mplot_cuts, mplot_density,
mplot_full, mplot_gain,
mplot_importance,
mplot_lineal, mplot_metrics,
mplot_response, mplot_roc,
mplot_splits, msplit
Other Exploratory: corr_cross,
corr_var, crosstab,
df_str, distr,
freqs_df, freqs,
get_tweets, missingness,
plot_cats, plot_df,
plot_nums, tree_var,
trendsRelated