CMA – a comprehensive Bioconductor package for supervised classification with high dimensional data

BMC Bioinformatics

Table 2 Overview of hyperparameter tuning in CMA.

Method	Name in CMA	Range	Signification
gbmCMA	n.trees	1, 2,...	number of base learners (decision trees)
LassoCMA	norm.fraction	[0;1]	relative bound imposed on the ℓ¹ norm on the weight vector
knnCMA	k	1, 2,...,\| $ℒ$ \|	number of nearest neighbours
nnetCMA	size	1, 2, ...	number of units in the hidden layer
scdaCMA	delta	ℝ⁺	shrinkage towards zero applied to the centroids
svmCMA	cost	ℝ⁺	cost: controls the violations of the margin of the hyperplane
	gamma	ℝ⁺	controls the width of the Gaussian kernel (if used)

The first column gives the method name, whereas the name of the hyperparameter in the CMA package is given in the second column. The third column gives the range of the parameter and the fourth column its signification.

ISSN: 1471-2105