Splits an H2OFrame object into train and test sets.

Performs Random Forest modeling for classification and regression tasks.

Performs Deep Learning modeling for classification and regression tasks.

Performs Gradient Boosting Machine (GBM) modeling for classification and regression tasks.

Performs K-means clustering.

To compute the frequency table of a column in an H2O data frame.

To compute the correlation matrix for numeric columns of an H2O data frame.

To display the structure of an H2O data frame, including column names, types, and summary statistics.

To retrieve the levels of a categorical column in an H2O data frame.

To retrieve the dimensions (number of rows and columns) of an H2O data frame.

To retrieve the column names of an H2O data frame.

To retrieve the column names of an H2O data frame.

To provide a detailed description of an H2O data frame, including column names, data types, number of missing values, summary statistics, and distribution of factors.

To compute summary statistics for an H2O data frame.

To merge two H2O data frames by common column names.

To upload a file into the H2O cluster’s key-value store.

To assign an H2OFrame to a key in the H2O cluster’s key-value store.

To import a file into H2O’s distributed key-value store.

To initialize an H2O cluster in R for distributed machine learning tasks.

To read a CSV file with a comma as the decimal point into a data frame.