A Web-based Parallel Implementation to Classify Multiclass Large Datasets
Rabie Ahmed1, Malek Rababah2, Mehtab Mehdi3, Mohammed Al-Shomrani4
1Rabie Ahmed, Department of Computer Science, Northern Border University/ College of Computing and Information Technology, Rafha, Saudi Arabia.
2Malek Rababah, Department of Computer Science, Northern Border University/ College of Computing and Information Technology, Rafha, Saudi Arabia.
3Mehtab Mehdi, Department of Computer Science, Northern Border University/ College of Computing and Information Technology, Rafha, Saudi Arabia.
4Mohammed Al-Shomrani, King Abdulaziz University, Faculty of Science, P. O. Box 80203, Jeddah 21589, Saudi Arabia.
Manuscript received on 15 April 2015 | Revised Manuscript received on 25 April 2015 | Manuscript Published on 30 April 2015 | PP: 245-248 | Volume-4 Issue-4, April 2015 | Retrieval Number: D3977044415/15©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Last few years are witnessed for growing the interest in Web-based Applications. Web applications typically interact with a back-end database to retrieve data to the user as dynamically generated output. In our work, an application is built for classification data sets, especially multi class large data sets, using parallel algorithm PMC-PBC-SVM. Our proposed application presents a general framework for data preprocessing, classification, and prediction. Our application gives an easy and interactive visual interface for classification multi class large data sets which will be useful for both technical and non-technical users.
Keywords: Web-Based Applications, Classification Algorithms, SVM, Parallel Processing, Multiclass Large Datasets.
Scope of the Article: Classification