Advances in Bioengineering and Biomedical Science Research(ABBSR)

Department of Cardiothoracic Surgery, Maastricht University Medical Center+, Maastricht, the, Netherlands

Publications

• Research Article   
  ROC-Tree Algorithm for Stratification of Binary Classifier Sets with Varied Discrimination Threshold
  Author(s): Y.M.Ganushchak*, P.J.C.Barenburg, J.G.Maessen and P. Sardari Nia
  
  Binary classifier systems are used in multiple practical situations. Evaluation of diagnostic ability of a binary classifier, as its discrimination threshold is varied, often requires data transformation by performing aggregation operations. One of the most used aggregation methods is division by percentiles which divides the data set at the equal by size subgroups blindly, independently from the structure of data. We developed a ROC-tree algorithm for selection of threshold values, which is a recursive downwards splitting of each group at the two subgroups (branches) by cut-off point of ROC curve. We showed that suggested ROC-tree algorithm allows to define optimal (natural) boundaries and number of groups. Two methods of data aggregation (percentiles and ROC-tree algorithms) were tested using the dataset ‘Credit Card Fraud Detection’ (https://www.kaggle.com/mlg.. Read More»
  

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