Implements Gaussian Processes for regression without hyperparameter-tuning. For more information see David J.C. Mackay (1998). Introduction to Gaussian Processes. Dept. of Physics, Cambridge University, UK.
(based on WEKA 3.6)
For further options, click the 'More' - button in the dialog.
All weka dialogs have a panel where you can specify classifier-specific parameters.
The Preliminary Attribute Check tests the underlying classifier against the DataTable specification at the inport of the node. Columns that are compatible with the classifier are marked with a green 'ok'. Columns which are potentially not compatible are assigned a red error message.
Important: If a column is marked as 'incompatible', it does not necessarily mean that the classifier cannot be executed! Sometimes, the error message 'Cannot handle String class' simply means that no nominal values are available (yet). This may change during execution of the predecessor nodes.
Capabilities: [Nominal attributes, Binary attributes, Unary attributes, Empty nominal attributes, Numeric attributes, Missing values, Numeric class, Date class, Missing class values] Dependencies: [Nominal attributes, Binary attributes, Unary attributes, Empty nominal attributes, Numeric attributes, Date attributes, String attributes, Relational attributes] min # Instance: 1
D: If set, classifier is run in debug mode and may output additional info to the console
L: Level of Gaussian Noise. (default: 1.0)
N: Whether to 0=normalize/1=standardize/2=neither. (default: 0=normalize)
K: The Kernel to use. (default: weka.classifiers.functions.supportVector.PolyKernel)
D: Enables debugging output (if available) to be printed. (default: off)
no-checks: Turns off all checks - use with caution! (default: checks on)
C: The size of the cache (a prime number), 0 for full cache and -1 to turn it off. (default: 250007)
G: The Gamma parameter. (default: 0.01)
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