makl_train: Train a Multiple Approximate Kernel Learning (MAKL) Model

In MAKL: Multiple Approximate Kernel Learning (MAKL)

Train a Multiple Approximate Kernel Learning (MAKL) Model

Description

Train a MAKL model to be used as an input to makl_test().

Usage

makl_train(
  X,
  y,
  D = 100,
  sigma_N = 1000,
  CV = 1,
  lambda_set = c(0.9, 0.8, 0.7, 0.6),
  membership
)

Arguments

X	training dataset, matrix of size N x d.
y	response vector of length N, containing only -1 and 1.
D	numeric value related to the number of random features to be used for approximation.
sigma_N	numeric value preferably smaller than N, used to calculate sigma to create random features.
CV	integer value between 0 and N. If CV is equal to 0 or 1, no cross validation is performed. If CV is greater than or equal to 2, CV is assigned as fold count in the cross validation.
lambda_set	a continuous number between 0 and 1, used for regularization.
membership	a list of length of number of groups, containing feature memberships to each group.

Value

a list containing the MAKL model and related parameters to be used in makl_test().

MAKL documentation built on July 6, 2022, 5:05 p.m.