feamiR (version 0.1.0)

svmsigmoid: Sigmoid SVM Implements a sigmoid SVM using general svm function (for ease of use in feature selection)

Description

Sigmoid SVM Implements a sigmoid SVM using general svm function (for ease of use in feature selection)

Usage

svmsigmoid(data_train, data_test, includeplot = FALSE)

Arguments

data_train

Training set: dataframe containing classification column and all other columns features. This is the dataset on which the decision tree model is trained.

data_test

Test set: dataframe containing classification column and all other columns features. This is the dataset on which the decision tree model in tested.

includeplot

Show performance scatter plot (default:FALSE)

Value

List containing performance percentages, accessed using training (training accuracy), test (test accuracy), trainsensitivity, testsensitivity, trainspecificity, testspecificity.

Examples

# NOT RUN {
data_train = data.frame(
      classification=as.factor(c(1,1,0,0,1,1,0,0,1,1)),
      A=c(1,1,1,0,0,0,1,1,1,0),
      B=c(0,1,1,0,1,1,0,1,1,0),
      C=c(0,0,1,0,0,1,0,0,1,0))
data_test = data.frame(
      classification=as.factor(c(1,1,0,0,1,1,1,0)),
      A=c(0,0,0,1,0,0,0,1),
      B=c(1,1,1,0,0,1,1,1),
      C=c(0,0,1,1,0,0,1,1))
svmsigmoid(data_train,data_test)
# }