Flow
weka.GaussianProcesses_PolyKernel

weka.GaussianProcesses_PolyKernel

Visibility: public Uploaded 30-03-2017 by Daan Dinkla Weka_3.8.1 0 runs
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
David J.C. Mackay (1998). Introduction to Gaussian Processes. Dept. of Physics, Cambridge University, UK.

Components

Kweka.PolyKernel(11)The Kernel to use. (default: weka.classifiers.functions.supportVector.PolyKernel)

Parameters

-do-not-check-capabilitiesIf set, classifier capabilities are not checked before classifier is built (use with caution).
CThe size of the cache (a prime number), 0 for full cache and -1 to turn it off. (default: 250007)
EThe Exponent to use. (default: 1.0)
KThe Kernel to use. (default: weka.classifiers.functions.supportVector.PolyKernel)default: weka.classifiers.functions.supportVector.PolyKernel
LLevel of Gaussian Noise wrt transformed target. (default 1)default: 1.0
NWhether to 0=normalize/1=standardize/2=neither. (default 0=normalize)default: 0
SRandom number seed. (default 1)default: 1
batch-sizeThe desired batch size for batch prediction (default 100).
no-checksTurns off all checks - use with caution! (default: checks on)
num-decimal-placesThe number of decimal places for the output of numbers in the model (default 2).
output-debug-infoIf set, classifier is run in debug mode and may output additional info to the console

0
Runs

List all runs
Parameter:
Rendering chart
Rendering table