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

## Documentation for package ‘Biocomb’ version 0.4

- DESCRIPTION file.

## Help Pages

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