summary.bootstrapValidation_Bin
(Package: FRESA.CAD) :
Generate a report of the results obtained using the bootstrapValidation_Bin function
This function prints two tables describing the results of the bootstrap-based validation of binary classification models. The first table reports the accuracy, sensitivity, specificity and area under the ROC curve (AUC) of the train and test data set, along with their confidence intervals. The second table reports the model coefficients and their corresponding integrated discrimination improvement (IDI) and net reclassification improvement (NRI) values.
● Data Source:
CranContrib
● Keywords: Model_Inspection
● Alias: summary, summary.bootstrapValidation_Bin
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crossValidationFeatureSelection_Bin
(Package: FRESA.CAD) :
IDI/NRI-based selection of a linear, logistic, or Cox proportional hazards regression model from a set of candidate variables
This function performs a cross-validation analysis of a feature selection algorithm based on the integrated discrimination improvement (IDI) or the net reclassification improvement (NRI) to return a predictive model. It is composed of an IDI/NRI-based feature selection followed by an update procedure, ending with a bootstrapping backwards feature elimination. The user can control how many train and blind test sets will be evaluated.
● Data Source:
CranContrib
● Keywords: Model_Generation
● Alias: crossValidationFeatureSelection_Bin
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ForwardSelection.Model.Res
(Package: FRESA.CAD) :
NeRI-based feature selection procedure for linear, logistic, or Cox proportional hazards regression models
This function performs a bootstrap sampling to rank the most frequent variables that statistically aid the models by minimizing the residuals. After the frequency rank, the function uses a forward selection procedure to create a final model, whose terms all have a significant contribution to the net residual improvement (NeRI).
● Data Source:
CranContrib
● Keywords: Model_Generation
● Alias: ForwardSelection.Model.Res
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FRESA.CAD-package
(Package: FRESA.CAD) :
FeatuRE Selection Algorithms for Computer-Aided Diagnosis (FRESA.CAD)
Contains a set of utilities for building and testing formula-based models for Computer Aided Diagnosis/prognosis applications via feature selection. Bootstrapped Stage Wise Model Selection (B:SWiMS) controls the false selection (FS) for linear, logistic, or Cox proportional hazards regression models. Utilities include functions for: univariate/longitudinal analysis, data conditioning (i.e. covariate adjustment and normalization), model validation and visualization.
● Data Source:
CranContrib
● Keywords: package
● Alias: FRESA.CAD, FRESA.CAD-package
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cancerVarNames
(Package: FRESA.CAD) :
Data frame used in several examples of this package
This data frame contains two columns, one with names of variables, and the other with descriptions of such variables. It is used in several examples of this package. Specifically, it is used in examples working with the stage C prostate cancer data from the rpart package
● Data Source:
CranContrib
● Keywords: Datasets
● Alias: cancerVarNames
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bootstrapValidation_Bin
(Package: FRESA.CAD) :
Bootstrap validation of binary classification models
This function bootstraps the model n times to estimate for each variable the empirical distribution of model coefficients, area under ROC curve (AUC), integrated discrimination improvement (IDI) and net reclassification improvement (NRI). At each bootstrap the non-observed data is predicted by the trained model, and statistics of the test prediction are stored and reported. The method keeps track of predictions and plots the bootstrap-validated ROC. It may plots the blind test accuracy, sensitivity, and specificity, contrasted with the bootstrapped trained distributions.
● Data Source:
CranContrib
● Keywords: Model_Diagnosis
● Alias: bootstrapValidation_Bin
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bootstrapVarElimination_Bin
(Package: FRESA.CAD) :
IDI/NRI-based backwards variable elimination with bootstrapping
This function removes model terms that do not improve the bootstrapped integrated discrimination improvement (IDI) or net reclassification improvement (NRI) significantly.
● Data Source:
CranContrib
● Keywords: Model_Generation
● Alias: bootstrapVarElimination_Bin
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This function removes model terms that do not significantly improve the "net residual" (NeRI)
● Data Source:
CranContrib
● Keywords: Model_Generation
● Alias: backVarElimination_Res
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This function fits a linear, logistic, or Cox proportional hazards regression model to given data
● Data Source:
CranContrib
● Keywords: Model_Inspection
● Alias: modelFitting
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updateModel.Res
(Package: FRESA.CAD) :
Update the NeRI-based model using new data or new threshold values
This function will take the frequency-ranked set of variables and will generate a new model with terms that meet the net residual improvement (NeRI) threshold criteria.
● Data Source:
CranContrib
● Keywords: Model_Generation
● Alias: updateModel.Res
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