title: Robust High-dimensional Bioinformatics Data Streams Mining by ODR-ioVFDT.
abstract: Outlier detection in bioinformatics data streaming mining has received significant attention by research communities in recent years. The problems of how to distinguish noise from an exception and deciding whether to discard it or to devise an extra decision path for accommodating it are causing dilemma. In this paper, we propose a novel algorithm called ODR with incrementally Optimized Very Fast Decision Tree (ODR-ioVFDT) for taking care of outliers in the progress of continuous data learning. By using an adaptive interquartile-range based identification method, a tolerance threshold is set. It is then used to judge if a data of exceptional value should be included for training or otherwise. This is different from the traditional outlier detection/removal approaches which are two separate steps in processing through the data. The proposed algorithm is tested using datasets of five bioinformatics scenarios and comparing the performance of our model and other ones without ODR. The results show that ODR-ioVFDT has better performance in classification accuracy, kappa statistics, and time consumption. The ODR-ioVFDT applied onto bioinformatics streaming data processing for detecting and quantifying the information of life phenomena, states, characters, variables and components of the organism can help to diagnose and treat disease more effectively.
authors.affiliation: Department of Computer and Information Science, Univeristy of Macau, SAR, Macau.
authors.forename: Dantong
authors.initials: D
authors.lastname: Wang
authors.affiliation: Department of Computer and Information Science, Univeristy of Macau, SAR, Macau.
authors.forename: Simon
authors.initials: S
authors.lastname: Fong
authors.affiliation: School of Computer Science and Engineering, University of New South Wales, Australia.
authors.forename: Raymond K
authors.initials: RK
authors.lastname: Wong
authors.affiliation: Department of Computer Science, Lakehead University, Thunder Bay, Canada.
authors.forename: Sabah
authors.initials: S
authors.lastname: Mohammed
authors.affiliation: Department of Computer Science, Lakehead University, Thunder Bay, Canada.
authors.forename: Jinan
authors.initials: J
authors.lastname: Fiaidhi
authors.affiliation: School of Medicine, University of Western Sydney, New South Wales, Australia.
authors.forename: Kelvin K L
authors.initials: KK
authors.lastname: Wong
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D057225:Data Mining / Q000379:methods*; D003658:Decision Making, Computer-Assisted