benchmark.data

<p>Datasets two groups, labels -1 and 1, with varying amounts of overlap.</p>

datasets

Provides R and C++ function that enable the user to conduct multiple
kernel learning (MKL) and cross validation for support vector machine (SVM) models.
Cross validation can be used to identify kernel shapes and hyperparameter
combinations that can be used as candidate kernels for MKL. There are three
implementations provided in this package, namely SimpleMKL Alain Rakotomamonjy et. al
(2008), Simple and Efficient MKL Xu et. al (2010), and Dual augmented Lagrangian MKL
Suzuki and Tomioka (2011) <doi:10.1007/s10994-011-5252-9>. These methods identify the convex combination of
candidate kernels to construct an optimal hyperplane.

Christopher Wilson

RMKL

Multiple Kernel Learning for Classification or Regression
Problems

benchmark.data function

<p>A list of dataframes with 3 columns and 200 samples, where the x and y
are generated from 2 multivariate distributions. The mean of the two groups vary,
to allow for different amount overlap for the groups.</p>

benchmark.data: Benchmark.data.

Description

Usage

Arguments

Format