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FRESA.CAD (version 2.0.2)

FeatuRE Selection Algorithms for Computer Aided Diagnosis

Description

Contains a set of utilities for building and testing formula-based models (linear, logistic or COX) for Computer Aided Diagnosis/Prognosis applications. Utilities include data adjustment, univariate analysis, model building, model-validation, longitudinal analysis, reporting and visualization.

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Version

Install

install.packages('FRESA.CAD')

Monthly Downloads

395

Version

2.0.2

License

LGPL (>= 2)

Maintainer

Jose Gerardo TamezPena

Last Published

February 22nd, 2015

Functions in FRESA.CAD (2.0.2)

crossValidationFeatureSelection

IDI/NRI-based selection of a linear, logistic, or Cox proportional hazards regression model from a set of candidate variables
featureAdjustment

Adjust each listed variable to the provided set of covariates
bootstrapValidationNeRI

Bootstrap validation of regression models
bootstrapVarNeRIElimination

NeRI-based backwards variable elimination with bootstrapping
plot.bootstrapValidation

Plot ROC curves of bootstrap results
rankInverseNormalDataFrame

Perform a z-transformation of the data using the rank-based inverse normal transformation
residualForNeRIs

Return residuals from prediction
heatMaps

Plot a heat map of selected variables
NeRIBasedFRESA.Model

NeRI-based feature selection procedure for linear, logistic, or Cox proportional hazards regression models
updateModel

Update the IDI/NRI-based model using new data or new threshold values
medianPredict

The median prediction from a list of models
plot.bootstrapValidationNeRI

Plot ROC curves of bootstrap results
summary.bootstrapValidation

Generate a report of the results obtained using the bootstrapValidation function
bootstrapVarElimination

IDI/NRI-based backwards variable elimination with bootstrapping
getVarReclassification

Analysis of the effect of each term of a binary classification model by analyzing its reclassification performance
backVarElimination

IDI/NRI-based backwards variable elimination
timeSerieAnalysis

Fit the listed time series variables to a given model
backVarNeRIElimination

NeRI-based backwards variable elimination
listTopCorrelatedVariables

List the variables that are highly correlated with each other
cancerVarNames

Data frame used in several examples of this package
getVarNeRI

Analysis of the effect of each term of a linear regression model by analyzing its residuals
summaryReport

Report the univariate analysis, the cross-validation analysis and the correlation analysis
ReclassificationFRESA.Model

IDI/NRI-based feature selection procedure for linear, logistic, and Cox proportional hazards regresion models
univariateRankVariables

Univariate analysis of features
plotModels.ROC

Plot test ROC curves of each cross-validation model
reportEquivalentVariables

Report the set of variables that will perform an equivalent IDI discriminant function
predictForFresa

Linear or probabilistic prediction
improvedResiduals

Estimate the significance of the reduction of predicted residuals
update.uniRankVar

Update the univariate analysis using new data
FRESA.CAD-package

FeatuRE Selection Algorithms for Computer-Aided Diagnosis (FRESA.CAD)
bootstrapValidation

Bootstrap validation of binary classification models
updateNeRIModel

Update the NeRI-based model using new data or new threshold values
getKNNpredictionFromFormula

Predict classification using KNN
crossValidationNeRIFeatureSelection

NeRI-based selection of a linear, logistic, or Cox proportional hazards regression model from a set of candidate variables
modelFitting

Fit a model to the data
FRESA.Model

Automated model selection
uniRankVar

Univariate analysis of features (additional values returned)