In order to select a set of features used for successful classification of two or more groups of samples, multiple classification and feature selection algorithms are utilised. By combining the results of all methods and applying a bootstrapping approach a robust set of features with high power to distinguish the sample groups is selected.
|Date of publication||2016-02-07 14:37:37|
|Maintainer||Christian Bender <firstname.lastname@example.org>|
align_feat_boruta: Create matrix with aligned feature sets from Boruta results.
align_features: Create matrix with aligned feature sets from SVM SCAD...
bootfs-package: Use multiple feature selection algorithms to derive robust...
bootstrap_roc: Create roc curves from bootstrapping classification results.
bsGBM: Wrapper for GBM bootstrapping
bsPAMR: Perform PAMR bootstrapping.
bsRFBORUTA: Perform RFBORUTA bootstrapping.
bsSCAD: Perform SCAD SVM bootstrapping.
bstr_multi: SVM SCAD bootstrapping classification and feature selection.
control_params: Create control parameter object for the classifiers
cvGBM: Make a crossvalidation using GBM.
cv_gbmclass: Internal crossvalidation method for GBM classification
cv_pamclass: Wrapper for PAMR classification call.
cvPAMR: Main wrapper to call PAMR crossvalidation.
cv_penalizedSVM: SVM SCAD crossvalidation.
cvRFBORUTA: Crossvalidation for Random Forests with Boruta feature...
cv_rfclass: Wrapper for RF Boruta classification crossvalidation.
cvSCAD: Crossvalidation for SCAD SVM classification and feature...
dist.eucsq: Squared euclidean distance metric. Used for ward clustering.
doBS: Perform bootstrapped feature selection with multiple...
doCV: Performance evaluation by crossvalidation for multiple...
drawheat: Wrapper for heatmap drawing.
extract_feat_boruta: Feature extraction for Boruta bootstrapping results.
extract_feat_pam: Feature extraction for PAMR bootstrapping results.
extract_feature_rankings: Feature ranking extraction for SVM SCAD bootstrapping...
extract_features: Helper for feature extraction.
extract_features_rf_boruta: Helper for feature extraction for RF Boruta.
extractsignatures: Helper for extracting all feature signatures from a...
fitGBM: Fit a Gradient Boosting Machine model.
gbm_multi: Calling function to GBM bootstrapping
get_ellipsis_a: Helper for importance graph drawing.
get_feature_ranking: Get a feature ranking. Helper for SVM SCAD feature...
get_pam_features: Helper for PAMR feature extraction.
importance_igraph: Graphically represent the (co-)occurrences of a set of...
layout.ellipsis: Layout function creating an ellipsis.
makeIG: Create an importance graph from a bootstrapping result of a...
resultBS: Summarise the results of a bootstrapping analysis.
resultCV: create a result plot for all performed crossvalidations
rf_multi: Wrapper for RF Boruta bootstrapping.
roc: Draw ROC curve.
run_pam: Wrapper for PAMR bootstrapping classification.
select_bootstrap_data: Select bootstrapping samples preserving group member...
select_cv_balanced: Balanced training/test set selection for crossvalidation.
select_threshold: Find optimal threshold for PAMR feature selection.
simDataSet: simDataSet - simulation of exemplary dataset
svmclass: Wrapper for SVM SCAD classification call.
ward: Clustering function using ward clustering.