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

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Documentation for package ‘Biocomb’ version 0.4

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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