SVM_cv: performs SVM classification and testing

In aspen-shen/CytoBinning:

Description

This function applies SVM in kernlab package to classify two groups of data points stored in two matrices, applies its classification boundary to testing dataset and outputs corresponding accuracy.

Usage

SVM_cv(controls, exper, feature_index, test.control, test.exp)

Arguments

controls	Training matrix of healthy cells to be classified
exper	Training matrix of diseased cells to be classified
feature_index	A vector contain index of measurements used in classification, should be a vector of integers, length must be larger than 1
test.control	Testing matrix of healthy cells
test.exp	Testing matrix of diseased cells

Value

accuracy Classificaiton accuracy of the training dataset

test Classification accuracy of the test dataset

weight Normalized weights of the features

aspen-shen/CytoBinning documentation built on May 17, 2019, 2:49 p.m.