Package: SVMMaj 0.2.9.2

SVMMaj: Implementation of the SVM-Maj Algorithm

Implements the SVM-Maj algorithm to train data with support vector machine <doi:10.1007/s11634-008-0020-9>. This algorithm uses two efficient updates, one for linear kernel and one for the nonlinear kernel.

Authors:Hoksan Yip [aut, cre], Patrick J.F. Groenen [aut], Georgi Nalbantov [aut]

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SVMMaj.pdf |SVMMaj.html✨
SVMMaj/json (API)

# Install 'SVMMaj' in R:

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

Datasets:

AusCredit - Australian Credit Approval Dataset
AusCredit.te - Australian Credit Approval Dataset
AusCredit.tr - Australian Credit Approval Dataset
diabetes - Pima Indians Diabetes Data Set
diabetes.te - Pima Indians Diabetes Data Set
diabetes.tr - Pima Indians Diabetes Data Set
supermarket1996 - Supermarket data 1996
voting - Congressional Voting Records Data Set
voting.te - Congressional Voting Records Data Set
voting.tr - Congressional Voting Records Data Set

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.06 score 1 stars 23 scripts 202 downloads 9 exports 38 dependencies

Last updated 3 months agofrom:2c15e8f5a1. Checks:OK: 7. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Oct 31 2024
R-4.5-win	OK	Oct 31 2024
R-4.5-linux	OK	Oct 31 2024
R-4.4-win	OK	Oct 31 2024
R-4.4-mac	OK	Oct 31 2024
R-4.3-win	OK	Oct 31 2024
R-4.3-mac	OK	Oct 31 2024

Exports:auc classification getHinge isb normalize plotWeights roccurve svmmaj svmmajcrossval

Dependencies:cli colorspace dplyr fansi farver generics ggplot2 glue gridExtra 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

paper

Rendered frompaper.Rnwusingutils::Sweaveon Oct 31 2024.

Last update: 2024-08-20
Started: 2018-02-25

Citation

Readme and manuals

Help Manual

Help page	Topics
Returns the area under the curve value	auc
Australian Credit Approval Dataset	AusCredit AusCredit.te AusCredit.tr
Show the classification performance	classification
Pima Indians Diabetes Data Set	diabetes diabetes.te diabetes.tr
Hinge error function of SVM-Maj	getHinge print.hinge
I-spline basis of each column of a given matrix	isb
Transform a given data into I-splines	isplinebasis
Normalize/standardize the columns of a matrix	normalize
Plot the hinge function	plot.hinge
Plot the cross validation output	plot.svmmajcrossval
Plot the weights of all attributes from the trained SVM model	plotWeights
Out-of-Sample Prediction from Unseen Data.	predict.svmmaj
Perform the transformation based on predefined settings	predict.transDat
SVM-Maj Algorithm	print.q.svmmaj svmmaj svmmaj.default
Print Svmmaj class	plot.svmmaj print.summary.svmmaj print.svmmaj summary.svmmaj
Print SVMMaj cross validation results	print.svmmajcrossval summary.svmmajcrossval
Plot the ROC curve of the predicted values	roccurve
Supermarket data 1996	supermarket1996
k-fold Cross-Validation of SVM-Maj	svmmajcrossval
Transform the data with normalization and/or spline basis	transformdata
Congressional Voting Records Data Set	voting voting.te voting.tr
Returns transformed attributes	X.svmmaj