Feature Selection and Classification with the Embedded Validation Procedures for Biomedical Data Analysis

Documentation for package ‘Biocomb’ version 0.4

Biocomb-package	Tools for Data Mining
Biocomb	Tools for Data Mining
CalcGene	Calculate HUM value
CalcROC	Calculate ROC points
Calculate3D	Plot the 3D-ROC curve
CalculateHUM_Ex	Calculate HUM value
CalculateHUM_Plot	Plot 2D-ROC curve
CalculateHUM_ROC	Compute the points for ROC curve
CalculateHUM_seq	Calculate HUM value
chi2.algorithm	Select the subset of features
classifier.loop	Classification and classifier validation
compute.auc.permutation	Calculates the p-values
compute.auc.random	Calculates the p-values
compute.aucs	Ranks the features
cost.curve	Plots the RCC curve for two-class problem
datasetF6	simulated data
data_test	simulated data
generate.data.miss	Generate the dataset with missing values
input_miss	Process the dataset with missing values
leukemia72	desease data
leukemia72_2	desease data
leukemia_miss	desease data
pauc	Calculates the p-values
pauclog	Calculates the p-values
plotClass.result	Plots the results of classifier validation schemes
plotRoc.curves	Plots the ROC curve for two-class problem
ProcessData	Select the subset of features
select.cfs	Select the subset of features
select.fast.filter	Select the subset of features
select.forward.Corr	Select the subset of features
select.forward.wrapper	Select the subset of features
select.inf.chi2	Ranks the features
select.inf.gain	Ranks the features
select.inf.symm	Ranks the features
select.process	Feature ranking and feature selection
select.relief	Ranks the features