Support vector machines study on english isolated-word-error classification and regression

A better understanding on word classification and regression could lead to a better detection and correction technique. We used different features or attributes to represent a machine-printed English word and support vector machines is used to evaluate those features into two class types of word: co...

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Main Authors: Hasan A.B., Kiong T.S., Paw J.K.S., Zulkifle A.K.
Other Authors: 55378583800
Format: Article
Published: Maxwell Science Publications 2023
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spelling my.uniten.dspace-301702023-12-29T15:45:12Z Support vector machines study on english isolated-word-error classification and regression Hasan A.B. Kiong T.S. Paw J.K.S. Zulkifle A.K. 55378583800 15128307800 22951210700 7801341335 Artificial intelligence Communication Statistical theory SVM kernel Artificial intelligence Chemical detection Communication Hamming distance Regression analysis Correction techniques English word Minimum edit distance Statistical theory Support vector SVM kernel Training process Word classification Support vector machines A better understanding on word classification and regression could lead to a better detection and correction technique. We used different features or attributes to represent a machine-printed English word and support vector machines is used to evaluate those features into two class types of word: correct and wrong word. Our proposed support vectors model classified the words by using fewer words during the training process because those training words are to be considered as personalized words. Those wrong words could be replaced by correct words predicted by the regression process. Our results are very encouraging when compared with neural networks, Hamming distance or minimum edit distance technique; with further improvement in sight. � Maxwell Scientific Organization, 2013. Final 2023-12-29T07:45:12Z 2023-12-29T07:45:12Z 2013 Article 10.19026/rjaset.5.4985 2-s2.0-84872775017 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84872775017&doi=10.19026%2frjaset.5.4985&partnerID=40&md5=2de99a6ce8a899c8fd7544beea1540b1 https://irepository.uniten.edu.my/handle/123456789/30170 5 2 531 537 All Open Access; Hybrid Gold Open Access Maxwell Science Publications Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic Artificial intelligence
Communication
Statistical theory
SVM kernel
Artificial intelligence
Chemical detection
Communication
Hamming distance
Regression analysis
Correction techniques
English word
Minimum edit distance
Statistical theory
Support vector
SVM kernel
Training process
Word classification
Support vector machines
spellingShingle Artificial intelligence
Communication
Statistical theory
SVM kernel
Artificial intelligence
Chemical detection
Communication
Hamming distance
Regression analysis
Correction techniques
English word
Minimum edit distance
Statistical theory
Support vector
SVM kernel
Training process
Word classification
Support vector machines
Hasan A.B.
Kiong T.S.
Paw J.K.S.
Zulkifle A.K.
Support vector machines study on english isolated-word-error classification and regression
description A better understanding on word classification and regression could lead to a better detection and correction technique. We used different features or attributes to represent a machine-printed English word and support vector machines is used to evaluate those features into two class types of word: correct and wrong word. Our proposed support vectors model classified the words by using fewer words during the training process because those training words are to be considered as personalized words. Those wrong words could be replaced by correct words predicted by the regression process. Our results are very encouraging when compared with neural networks, Hamming distance or minimum edit distance technique; with further improvement in sight. � Maxwell Scientific Organization, 2013.
author2 55378583800
author_facet 55378583800
Hasan A.B.
Kiong T.S.
Paw J.K.S.
Zulkifle A.K.
format Article
author Hasan A.B.
Kiong T.S.
Paw J.K.S.
Zulkifle A.K.
author_sort Hasan A.B.
title Support vector machines study on english isolated-word-error classification and regression
title_short Support vector machines study on english isolated-word-error classification and regression
title_full Support vector machines study on english isolated-word-error classification and regression
title_fullStr Support vector machines study on english isolated-word-error classification and regression
title_full_unstemmed Support vector machines study on english isolated-word-error classification and regression
title_sort support vector machines study on english isolated-word-error classification and regression
publisher Maxwell Science Publications
publishDate 2023
_version_ 1806426693654544384
score 13.214268