Package: kerntools 1.2.0

kerntools: Kernel Functions and Tools for Machine Learning Applications

Kernel functions for diverse types of data (including, but not restricted to: nonnegative and real vectors, real matrices, categorical and ordinal variables, sets, strings), plus other utilities like kernel similarity, kernel Principal Components Analysis (PCA) and features' importance for Support Vector Machines (SVMs), which expand other 'R' packages like 'kernlab'.

Authors:Elies Ramon [aut, cre, cph]

kerntools_1.2.0.tar.gz
kerntools_1.2.0.zip(r-4.5)kerntools_1.2.0.zip(r-4.4)kerntools_1.2.0.zip(r-4.3)
kerntools_1.2.0.tgz(r-4.5-any)kerntools_1.2.0.tgz(r-4.4-any)kerntools_1.2.0.tgz(r-4.3-any)
kerntools_1.2.0.tar.gz(r-4.5-noble)kerntools_1.2.0.tar.gz(r-4.4-noble)
kerntools_1.2.0.tgz(r-4.4-emscripten)kerntools_1.2.0.tgz(r-4.3-emscripten)
kerntools.pdf |kerntools.html✨
kerntools/json (API)
NEWS

# Install 'kerntools' in R:

install.packages('kerntools', repos = c('https://elies-ramon.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/elies-ramon/kerntools/issues

Pkgdown site:https://elies-ramon.github.io

Datasets:

showdata - Showdata
soil - Soil microbiota

On CRAN:

kernel-methods pca

4.73 score 1 stars 12 scripts 544 downloads 47 exports 37 dependencies

Last updated 16 days agofrom:a40da56366. Checks:9 OK. Indexed: yes.

Target	Result	Latest binary
Doc / Vignettes	OK	Mar 06 2025
R-4.5-win	OK	Mar 06 2025
R-4.5-mac	OK	Mar 06 2025
R-4.5-linux	OK	Mar 06 2025
R-4.4-win	OK	Mar 06 2025
R-4.4-mac	OK	Mar 06 2025
R-4.4-linux	OK	Mar 06 2025
R-4.3-win	OK	Mar 06 2025
R-4.3-mac	OK	Mar 06 2025

Exports:Acc Acc_rnd aggregate_imp Aitchison Boots_CI BrayCurtis centerK centerX Chi2 cLinear cosNorm cosnormX desparsify Dirac dummy_data dummy_var estimate_gamma F1 Frobenius frobNorm heatK histK Intersect Jaccard Kendall kPCA kPCA_arrows kPCA_imp KTA Laplace Linear minmax MKC nmse Normal_CI plotImp Prec Procrustes RBF Rec Ruzicka simK Spe Spectrum svm_imp TSS vonNeumann

Dependencies:cli colorspace dplyr fansi farver generics ggplot2 glue gtable isoband kernlab labeling lattice lifecycle magrittr MASS Matrix mgcv munsell nlme pillar pkgconfig plyr R6 RColorBrewer Rcpp reshape2 rlang scales stringi stringr tibble tidyselect utf8 vctrs viridisLite withr

Kernel functions

Elies Ramon

Rendered fromKernel-functions.Rmdusingknitr::rmarkdownon Mar 06 2025.

Last update: 2025-02-19
Started: 2024-10-25

Kernel PCA and Coinertia

Elies Ramon

Rendered fromKernel-PCA-and-CIA.Rmdusingknitr::rmarkdownon Mar 06 2025.

Last update: 2024-10-25
Started: 2024-10-25

kerntools: R tools for kernel methods

Elies Ramon

Rendered fromkerntools.Rmdusingknitr::rmarkdownon Mar 06 2025.

Last update: 2025-02-19
Started: 2024-09-11

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Accuracy	Acc
Accuracy of a random model	Acc_rnd
Aggregate importances	aggregate_imp
Confidence Interval using Bootstrap	Boots_CI
Kernels for count data	BrayCurtis Ruzicka
Centering a kernel matrix	centerK
Centering a squared matrix by row or column	centerX
Chi-squared kernel	Chi2
Compositional kernels	Aitchison cLinear
Cosine normalization of a kernel matrix	cosNorm
Cosine normalization of a matrix	cosnormX
This function deletes those columns and/or rows in a matrix/data.frame that only contain 0s.	desparsify
Kernels for categorical variables	Dirac
Convert categorical data to dummies.	dummy_data
Levels per factor variable	dummy_var
Gamma hyperparameter estimation (RBF kernel)	estimate_gamma
F1 score	F1
Frobenius kernel	Frobenius
Frobenius normalization	frobNorm
Kernel matrix heatmap	heatK
Kernel matrix histogram	histK
Kernels for sets	Intersect Jaccard
Kendall's tau kernel	Kendall
Kernel PCA	kPCA
Plot the original variables' contribution to a PCA plot	kPCA_arrows
Contributions of the variables to the Principal Components ("loadings")	kPCA_imp
Kernel-target alignment	KTA
Laplacian kernel	Laplace
Linear kernel	Linear
Minmax normalization	minmax
Multiple Kernel (Matrices) Combination	MKC
NMSE (Normalized Mean Squared Error)	nmse
Confidence Interval using Normal Approximation	Normal_CI
Importance barplot	plotImp
Precision or PPV	Prec
Procrustes Analysis	Procrustes
Gaussian RBF (Radial Basis Function) kernel	RBF
Recall or Sensitivity or TPR	Rec
Showdata	showdata
Kernel matrix similarity	simK
Soil microbiota (raw counts)	soil
Specificity or TNR	Spe
Spectrum kernel	Spectrum
SVM feature importance	svm_imp
Total Sum Scaling	TSS
Von Neumann entropy	vonNeumann

Package: kerntools 1.2.0

kerntools: Kernel Functions and Tools for Machine Learning Applications

Kernel functions

Kernel PCA and Coinertia

kerntools: R tools for kernel methods

Citation

Development and contributors

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)