This function lets the user create a robust and fast model, using H2O's AutoML function. The result is a list with the best model, its parameters, datasets, performance metrics, variables importances, and others.
h2o_automl(df, train_test = NA, split = 0.7, seed = 0, thresh = 5,
max_time = 5 * 60, max_models = 25, alarm = TRUE, export = FALSE,
plot = FALSE, project = "Machine Learning Model")Dataframe. Dataframe containing all your data, including the independent variable labeled as 'tag'
Character. If needed, df's column name with 'test' and 'train' values to split
Numeric. Value between 0 and 1 to split as train/test datasets. Value is for training set.
Numeric. Seed for random stuff and reproducibility
Integer. Threshold for selecting binary or regression models: this number is the threshold of unique values we should have in 'tag' (more than: regression; less than: classification)
Numeric. Max seconds you wish for the function to iterate
Numeric. Max models you wish for the function to create
Boolean. Ping an alarm when ready!
Boolean. Do you wish to save results into your working directory?
Boolean. Do you want to plot the results with mplot_full function?
Character. Your project's name