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Modified Multi-Class Miner using Particle of Swarm Optimization for Stream Data Classification
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 90 - Number 7 |
| Year of Publication: 2014 |
| Authors: Archana Bopche, Parmalik Kumar |
10.5120/15589-4353
|
Archana Bopche, Parmalik Kumar . Modified Multi-Class Miner using Particle of Swarm Optimization for Stream Data Classification. International Journal of Computer Applications. 90, 7 ( March 2014), 44-47. DOI=10.5120/15589-4353
Abstract
Multi-class miner is well recognized method for stream data classification. For the process of multi-class miner evaluation of new feature during classification is major problem. The problem of feature evaluation decreases the performance of multi-class miner (MCM). For the improvement of multi-class miner particle of swarm optimization technique is used. Particle of swarm optimization controls the dynamic feature evaluation process and decreases the possibility of confusion in selection of class and increase the classification ratio of multi-class miner. Particle of swarm optimization work in two phases one used as dynamic population selection and another are used for optimization process of evolved new feature. For the performance evaluation modified MCM algorithm implemented in MATLAB. For the validation of modified multi-class miner (MMCM) used sample dataset from UCI machine learning repository . Our empirical evaluation shows that better result in compression of multi-class miner and also increases the classification ratio of stream data classification.
References
- Urvesh Bhowan, Mark Johnston, Mengjie Zhang and Xin Yao "Evolving Diverse Ensembles using Genetic Programming for Classification with Unbalanced Data" in IEEE Tansaction2010.
- Yan-Nei Law and Carlo Zanily entitled" An Adaptive Nearest Neighbor Classification Algorithm for Data Streams" in PKDD 2005, LNAI 3721, pp. 108–120, 2005.
- Mohammad M. Masud, Latifur Khan, Bhavani Thuraisingham entilied "Classification And Novel Class Detection In Concept-Drifting Data Streams Under Time Constraints" in IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 23, NO. 6, JUNE 2011.
- Mohammad M. Masud, Qing Chen, Latifur Khan, Charu Aggarwal and Jing Gao , Jiawei Han and Bhavani Thuraisingham "Addressing Concept-Evolution in Concept-Drifting Data Streams " in IEEE Transaction 2010.
- Valerio Grossi, Alessandro Sperduti "Kernel-Based Selective Ensemble Learning for Streams of Trees" in Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence 2010.
- Li Su Xi, Hong-yan Liu, Zhen-Hui Song. "A New Classification Algorithm for Data Stream".
- Clay Woolam, Mohammad M. Masud, and Latifur Khan "Lacking Labels in the Stream: Classifying Evolving Stream Data with Few Labels" in I. J. Modern Education and Computer Science, 2011.
- Mohammad M. Masud, Qing Chen, Jing Gao, Latifur Khan, Jiawei Han, and Bhavani Thuraisingham "Classification and Novel Class Detection of Data Streams in a Dynamic Feature Space" in ISMIS 2009, LNAI 5722, pp. 552.
- Charu C. Aggarwal ,Jiawei Han, Jianyong Wang, Philip S. Yu "A Framework for On-Demand Classification of Evolving Data Streams" in ECML PKDD 2010, Part II, LNAI 6322, pp. 337–352.
- A. Azadeh , M. Saberi , A. Kazemc, V. Ebrahimipour , A. Nourmohammadzadeh, Z. Saberi "A ?exible algorithm for fault diagnosis in a centrifugal pump with corrupted data and noise based on ANN and support vector machine with hyper-parameters optimization" Applied Soft Computing, Elsevier ltd. 2013. Pp 1478-1485.
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