Conference Proceedings

ROC-tree: A novel decision tree induction algorithm based on receiver operating characteristics to classify gene expression data

MM Hossain, MR Hassan, J Bailey

Society for Industrial and Applied Mathematics - 8th SIAM International Conference on Data Mining 2008, Proceedings in Applied Mathematics 130 | Published : 2008


Gene expression information from microarray experiments is a primary form of data for biological analysis and can offer insights into disease processes and cellular behaviour. Such datasets are particularly challenging to build classifiers for, due to their very high dimensional nature and small sample size. Decision trees are a seemingly attractive technique for this domain, due to their easily interpretable white box nature and noise resistance. However, existing decision tree methods tend to perform rather poorly for classifying gene expression data. To address this gap, we introduce a new technique for building decision trees that is better suited to this scenario. Our method is based on..

View full abstract