Methods that produce a classification rule based on a convex combination of candidate kernels are referred to as multiple kernel learning (MKL) methods. You can install RMKL from GitHub. If you already have a previous version of RMKL installed, you can use that to …

Methods that produce a classification rule based on a convex combination of candidate kernels are referred to as multiple kernel learning (MKL) methods. You can install RMKL from GitHub. If you already have a previous version of RMKL installed, you can use that to …

2019年5月2日 · 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.

2019年5月2日 · Methods that produce a classification rule based on a convex combination of candidate kernels are referred to as multiple kernel learning (MKL) methods. You can install RMKL from GitHub. If you already have a previous version of RMKL installed, you can use that to install the new version:

:exclamation: This is a read-only mirror of the CRAN R package repository. RMKL — Multiple Kernel Learning for Classification or Regression Problems - cran/RMKL

2019年5月2日 · In RMKL: Multiple Kernel Learning for Classification or Regression Problems. Description Usage Arguments Value Examples. View source: R/SimpleMKL.Classification.R. Description. This function conducts Simple MKL for precomputed gramm matrices Usage

2012年1月17日 · In this paper, we address the MKL for classification in hyperspectral images by extracting the most variation from the space spanned by multiple kernels and propose a representative MKL (RMKL) algorithm.

:exclamation: This is a read-only mirror of the CRAN R package repository. RMKL — Multiple Kernel Learning for Classification or Regression Problems - cran/RMKL

2019年8月15日 · We present an R package, RMKL, which can implement cross-validation for training SVM and support vector regression models, as well as MKL for both classification and regression problems. Our package is equipped with implementations of SimpleMKL, SEMKL, and DALMKL under two loss functions.

2019年7月2日 · Here we present web-rMKL, a web server that provides an integrative dimensionality reduction with subsequent clustering of samples based on data from multiple inputs. The underlying machine learning method rMKL-LPP performed best for clinical enrichment in a recent benchmark of state-of-the-art multi-view clustering algorithms.