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GaussianProcesses (3.7)

Analytics Integrations Weka Weka (3.7) Classification Algorithms
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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.

Node details

Input ports
  1. Type: Table
    Training data
    Training data
Output ports
  1. Type: Weka 3.7 Classifier
    Trained model
    Trained model

Extension

The GaussianProcesses (3.7) node is part of this extension:

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