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Hybrid ensemble approach for classification

หน่วยงาน Central Queensland University, Australia

รายละเอียด

ชื่อเรื่อง : Hybrid ensemble approach for classification
นักวิจัย : Verma, Brijesh. , Hassan, Syed Zahid.
คำค้น : Neural networks (Computer science) , Applied research. , 890202 Application Tools and System Utilities. , 080109 Pattern Recognition and Data Mining. , 080108 Neural, Evolutionary and Fuzzy Computation. , Medical informatics. , Pattern perception. , Classifiers -- Ensembles -- Hybrid systems -- Neural networks -- Medical data classification
หน่วยงาน : Central Queensland University, Australia
ผู้ร่วมงาน : -
ปีพิมพ์ : 2552
อ้างอิง : http://hdl.cqu.edu.au/10018/43252
ที่มา : Verma, B & Hassan, S 2009, 'Hybrid Ensemble Approach for Classification', Applied Intelligence http://dx.doi.org/10.1007/s10489-009-0194-7 (viewed 19/4/10)
ความเชี่ยวชาญ : -
ความสัมพันธ์ : Applied intelligence. Netherlands. : Springer Netherlands, 2009. (September 19, 2009), 21 pages Refereed 0924-669X 1573-7497 (online) , ACQUIRE [electronic resource] : Central Queensland University Institutional Repository.
ขอบเขตของเนื้อหา : -
บทคัดย่อ/คำอธิบาย :

This paper presents a novel hybrid ensemble approach for classification in medical databases. The proposed approach is formulated to cluster extracted features from medical databases into soft clusters using unsupervised learning strategies and fuse the decisions using parallel data fusion techniques. The idea is to observe associations in the features and fuse the decisions made by learning algorithms to find the strong clusters which can make impact on overall classification accuracy. The novel techniques such as parallel neural-based strong clusters fusion and parallel neural network based data fusion are proposed that allow integration of various clustering algorithms for hybrid ensemble approach. The proposed approach has been implemented and evaluated on the benchmark databases such as Digital Database for Screening Mammograms, Wisconsin Breast Cancer, and Pima Indian Diabetics. A comparative performance analysis of the proposed approach with other existing approaches for knowledge extraction and classification is presented. The experimental results demonstrate the effectiveness of the proposed approach in terms of improved classification accuracy on benchmark medical databases.

บรรณานุกรม :
Verma, Brijesh. , Hassan, Syed Zahid. . (2552). Hybrid ensemble approach for classification.
    กรุงเทพมหานคร : Central Queensland University, Australia.
Verma, Brijesh. , Hassan, Syed Zahid. . 2552. "Hybrid ensemble approach for classification".
    กรุงเทพมหานคร : Central Queensland University, Australia.
Verma, Brijesh. , Hassan, Syed Zahid. . "Hybrid ensemble approach for classification."
    กรุงเทพมหานคร : Central Queensland University, Australia, 2552. Print.
Verma, Brijesh. , Hassan, Syed Zahid. . Hybrid ensemble approach for classification. กรุงเทพมหานคร : Central Queensland University, Australia; 2552.