LinearTSVMSSLR {SSLR}

General Interface for LinearTSVM model

Description

model from RSSL package Implementation of the Linear Support Vector Classifier. Can be solved in the Dual formulation, which is equivalent to SVM or the Primal formulation.

Usage

LinearTSVMSSLR(
  C = 1,
  Cstar = 0.1,
  s = 0,
  x_center = FALSE,
  scale = FALSE,
  eps = 1e-06,
  verbose = FALSE,
  init = NULL
)

Arguments

C

Cost variable

Cstar

numeric; Cost parameter of the unlabeled objects

s

numeric; parameter controlling the loss function of the unlabeled objects

x_center

logical; Should the features be centered?

scale

Whether a z-transform should be applied (default: TRUE)

eps

Small value to ensure positive definiteness of the matrix in QP formulation

verbose

logical; Controls the verbosity of the output

init

numeric; Initial classifier parameters to start the convex concave procedure

Examples

library(tidyverse)
library(caret)
library(tidymodels)
library(SSLR)

data(breast)

set.seed(1)
train.index <- createDataPartition(breast$Class, p = .7, list = FALSE)
train <- breast[ train.index,]
test  <- breast[-train.index,]

cls <- which(colnames(breast) == "Class")

#% LABELED
labeled.index <- createDataPartition(breast$Class, p = .2, list = FALSE)
train[-labeled.index,cls] <- NA


m <- LinearTSVMSSLR() %>% fit(Class ~ ., data = train)


#Accesing model from RSSL
model <- m$model