Man pages for SVMMaj
Implementation of the SVM-Maj Algorithm

aucReturns the area under the curve value
AusCreditAustralian Credit Approval Dataset
classificationShow the classification performance
diabetesPima Indians Diabetes Data Set
getHingeHinge error function of SVM-Maj
isbI-spline basis of each column of a given matrix
isplinebasisTransform a given data into I-splines
normalizeNormalize/standardize the columns of a matrix
plot.hingePlot the hinge function
plot.svmmajcrossvalPlot the cross validation output
plotWeightsPlot the weights of all attributes from the trained SVM model
predict.svmmajOut-of-Sample Prediction from Unseen Data.
predict.transDatPerform the transformation based on predefined settings
print.svmmajPrint Svmmaj class
print.svmmajcrossvalPrint SVMMaj cross validation results
roccurvePlot the ROC curve of the predicted values
supermarket1996Supermarket data 1996
svmmajSVM-Maj Algorithm
svmmajcrossvalk-fold Cross-Validation of SVM-Maj
transformdataTransform the data with normalization and/or spline basis
votingCongressional Voting Records Data Set
X.svmmajReturns transformed attributes
SVMMaj documentation built on May 2, 2019, 9:58 a.m.