H2O MOJO Predictor (Classification)

This node applies a classification MOJO (binomial or multinomial) to an input dataset.

Options

General Settings

Enforce presence of all feature columns

If checked, the node will fail if any of the feature columns used for learning the MOJO is missing. Otherwise, a warning will be displayed and the missing columns are treated as NA by the MOJO predictor.

Fail if a prediction exception occurs

If checked, the node will fail if the prediction of a row fails. Otherwise, a missing value will be the output and a warning will be given.

Treat unknown categorical values as missing values

By default, H2O does not handle the case that a categorical feature column contains a value that was not present during model training. If this option is enabled, H2O will convert these values to NA, i.e. treat them as missing values. If this option is disabled, the node will either fail or missing values will be in the output depending on the setting "Fail if a prediction exception occurs".

Classification Settings

Change prediction column name

Change the name of the prediction column.

Append individual class probabilities

Select to append the class probabilities of each class to the table. Useful for scoring models.

Suffix for probability columns

If class probabilities are appended, the suffix allows you to avoid duplicate column names. Can be empty.

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