GaussianProcesses (3.7)

Learner

Implements Gaussian processes for regression without hyperparameter-tuning

To make choosing an appropriate noise level easier, this implementation applies normalization/standardization to the target attribute as well as the other attributes (if normalization/standardizaton is turned on).Missing values are replaced by the global mean/mode.

Nominal attributes are converted to binary ones.Note that kernel caching is turned off if the kernel used implements CachedKernel.

(based on WEKA 3.7)

For further options, click the 'More' - button in the dialog.

All weka dialogs have a panel where you can specify classifier-specific parameters.

Input Ports

  1. Type: Data
    Training data

Output Ports

  1. Type: Weka 3.7 Classifier
    Trained model

Extension

This node is part of the extension

KNIME Weka Data Mining Integration (3.7)

v4.0.0

Short Link

Drag node into KNIME Analytics Platform