Recognition of Off-Line Handwritten Chinese Character by Using Decision Tree Based on Hiberarchy Decomposition
Decision tree based on hiberarchy decomposition is a kind of improved ID3 algorithm. It splits the training set by choosing different key attributes in different layers according to the correlation between classes and attributes. Compared with traditional ID3 algorithm, its rules are simpler and mor...
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| creator | Dong Liu Xiangnian Huang |
| description | Decision tree based on hiberarchy decomposition is a kind of improved ID3 algorithm. It splits the training set by choosing different key attributes in different layers according to the correlation between classes and attributes. Compared with traditional ID3 algorithm, its rules are simpler and more general. This paper uses the hiberarchy decomposition methods as well as the C4.5 algorithm and makes some adjustments to deal with the recognition of off-line handwritten Chinese character by constructing a multi-level decision tree. At last, get a scheme of rough classification and analyze the results with different attributes. Compared with the single decision tree, the decision tree based on hiberarchy decomposition has more advantages when dealing with the multi-class problem. Experiment results show that this new method has better accuracy rate. |
| doi_str_mv | 10.1109/ICACC.2009.21 |
| format | Conference Proceeding |
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It splits the training set by choosing different key attributes in different layers according to the correlation between classes and attributes. Compared with traditional ID3 algorithm, its rules are simpler and more general. This paper uses the hiberarchy decomposition methods as well as the C4.5 algorithm and makes some adjustments to deal with the recognition of off-line handwritten Chinese character by constructing a multi-level decision tree. At last, get a scheme of rough classification and analyze the results with different attributes. Compared with the single decision tree, the decision tree based on hiberarchy decomposition has more advantages when dealing with the multi-class problem. 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It splits the training set by choosing different key attributes in different layers according to the correlation between classes and attributes. Compared with traditional ID3 algorithm, its rules are simpler and more general. This paper uses the hiberarchy decomposition methods as well as the C4.5 algorithm and makes some adjustments to deal with the recognition of off-line handwritten Chinese character by constructing a multi-level decision tree. At last, get a scheme of rough classification and analyze the results with different attributes. Compared with the single decision tree, the decision tree based on hiberarchy decomposition has more advantages when dealing with the multi-class problem. Experiment results show that this new method has better accuracy rate.</description><subject>Character recognition</subject><subject>Cities and towns</subject><subject>Classification tree analysis</subject><subject>decision tree</subject><subject>Decision trees</subject><subject>Feature extraction</subject><subject>Handwriting recognition</subject><subject>hiberarchy decomposition</subject><subject>Mathematics</subject><subject>Pattern recognition</subject><subject>recognition of off-line handwritten Chinese character</subject><subject>Testing</subject><subject>Training data</subject><isbn>9781424433308</isbn><isbn>076953516X</isbn><isbn>9780769535166</isbn><isbn>1424433304</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2009</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotT01LAzEUDEhBrXv05CV_YGu-P466aisUCtKeSzb7to3YbEkWZP-9qfouw5s384ZB6J6SBaXEPr43T02zYITYBaNXqLLaUMGE4JwTM0O35WIssULxa1Tl_EnKCMkMZTcofoAfDjGMYYh46PGm7-t1iIBXLnbfKYwjRNwcC5OhoEvOj5BwO-FdDvGAX8CHfPFuEwB-dhk6XLZVaCG55I_TRTGczkP-jbhDs959Zaj-cY52b6_bZlWvN8tSY10HquVYO937jlKpGVjZKmqlNl0rOKOWcgvacDBAVFsEkilmFe2J9tKTVnRWMcnn6OHvbwCA_TmFk0vTXmituZL8Byt_WK4</recordid><startdate>200901</startdate><enddate>200901</enddate><creator>Dong Liu</creator><creator>Xiangnian Huang</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200901</creationdate><title>Recognition of Off-Line Handwritten Chinese Character by Using Decision Tree Based on Hiberarchy Decomposition</title><author>Dong Liu ; Xiangnian Huang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-a7fcd11572e95b619578db43219139e783e8e06b5725262961f07c5c0b4d96253</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Character recognition</topic><topic>Cities and towns</topic><topic>Classification tree analysis</topic><topic>decision tree</topic><topic>Decision trees</topic><topic>Feature extraction</topic><topic>Handwriting recognition</topic><topic>hiberarchy decomposition</topic><topic>Mathematics</topic><topic>Pattern recognition</topic><topic>recognition of off-line handwritten Chinese character</topic><topic>Testing</topic><topic>Training data</topic><toplevel>online_resources</toplevel><creatorcontrib>Dong Liu</creatorcontrib><creatorcontrib>Xiangnian Huang</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Dong Liu</au><au>Xiangnian Huang</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Recognition of Off-Line Handwritten Chinese Character by Using Decision Tree Based on Hiberarchy Decomposition</atitle><btitle>2009 International Conference on Advanced Computer Control</btitle><stitle>ICACC</stitle><date>2009-01</date><risdate>2009</risdate><spage>351</spage><epage>354</epage><pages>351-354</pages><isbn>9781424433308</isbn><isbn>076953516X</isbn><isbn>9780769535166</isbn><isbn>1424433304</isbn><abstract>Decision tree based on hiberarchy decomposition is a kind of improved ID3 algorithm. It splits the training set by choosing different key attributes in different layers according to the correlation between classes and attributes. Compared with traditional ID3 algorithm, its rules are simpler and more general. This paper uses the hiberarchy decomposition methods as well as the C4.5 algorithm and makes some adjustments to deal with the recognition of off-line handwritten Chinese character by constructing a multi-level decision tree. At last, get a scheme of rough classification and analyze the results with different attributes. Compared with the single decision tree, the decision tree based on hiberarchy decomposition has more advantages when dealing with the multi-class problem. Experiment results show that this new method has better accuracy rate.</abstract><pub>IEEE</pub><doi>10.1109/ICACC.2009.21</doi><tpages>4</tpages></addata></record> |
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| subjects | Character recognition Cities and towns Classification tree analysis decision tree Decision trees Feature extraction Handwriting recognition hiberarchy decomposition Mathematics Pattern recognition recognition of off-line handwritten Chinese character Testing Training data |
| title | Recognition of Off-Line Handwritten Chinese Character by Using Decision Tree Based on Hiberarchy Decomposition |
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