{"created":"2020-09-01T13:13:35.187000+00:00","id":3631,"links":{},"metadata":{"_buckets":{"deposit":"4de8e093-01dc-4af1-abb8-0318f436051c"},"_deposit":{"id":"3631","owners":[],"pid":{"revision_id":0,"type":"recid","value":"3631"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/3631","sets":["1582963302567:1597824273898"]},"communities":["ucsy"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"Comparative Study of C4.5 and Boosting using Decision Tree Learning Algorithm","subitem_1551255648112":"en"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"Data Mining aims to discover novel, interesting, and usefulknowledge and patterns from databases. Classification is a data mining techniquewhich addresses the problem of constructing a predication model for a classattribute given the values of other attributes and some examples of records withknown class. Decision tree are one of the most well-established classificationmethods. They are so popular because their ability to handle nisy data, theircomprehensibility, and their capability to learn disjunctive expression. One of themost popular decision tree construction algorithm is C4.5. The idea of esemblemethodology is to build a predictive model by integrating multiple models forbetter generalization error. It is well known that ensemble method can be used forimproving the predictive performance. Boosting is one of the methods for buildensemble of classifier. This paper compare s the popular C4.5 and boosted C4.5for their prediction accuracy using holdout method."}]},"item_1583103108160":{"attribute_name":"Keywords","attribute_value":[]},"item_1583103120197":{"attribute_name":"Files","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2019-07-26"}],"displaytype":"preview","filename":"Comparative Study of C4.pdf","filesize":[{"value":"6 Kb"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://meral.edu.mm/record/3631/files/Comparative Study of C4.pdf"},"version_id":"e92a8ab5-79f0-4e1a-9022-2432ad090fa7"}]},"item_1583103131163":{"attribute_name":"Journal articles","attribute_value_mlt":[{"subitem_issue":"","subitem_journal_title":"Sixth Local Conference on Parallel and Soft Computing","subitem_pages":"","subitem_volume":""}]},"item_1583103147082":{"attribute_name":"Conference papers","attribute_value_mlt":[{"subitem_acronym":"","subitem_c_date":"","subitem_conference_title":"","subitem_part":"","subitem_place":"","subitem_session":"","subitem_website":""}]},"item_1583103211336":{"attribute_name":"Books/reports/chapters","attribute_value_mlt":[{"subitem_book_title":"","subitem_isbn":"","subitem_pages":"","subitem_place":"","subitem_publisher":""}]},"item_1583103233624":{"attribute_name":"Thesis/dissertations","attribute_value_mlt":[{"subitem_awarding_university":"","subitem_supervisor(s)":[{"subitem_supervisor":""}]}]},"item_1583105942107":{"attribute_name":"Authors","attribute_value_mlt":[{"subitem_authors":[{"subitem_authors_fullname":"Tun, Thinzar"},{"subitem_authors_fullname":"Win, Chit Nilar"}]}]},"item_1583108359239":{"attribute_name":"Upload type","attribute_value_mlt":[{"interim":"Publication"}]},"item_1583108428133":{"attribute_name":"Publication type","attribute_value_mlt":[{"interim":"Article"}]},"item_1583159729339":{"attribute_name":"Publication date","attribute_value":"2011-12-29"},"item_1583159847033":{"attribute_name":"Identifier","attribute_value":"http://onlineresource.ucsy.edu.mm/handle/123456789/1363"},"item_title":"Comparative Study of C4.5 and Boosting using Decision Tree Learning Algorithm","item_type_id":"21","owner":"1","path":["1597824273898"],"publish_date":"2019-07-26","publish_status":"0","recid":"3631","relation_version_is_last":true,"title":["Comparative Study of C4.5 and Boosting using Decision Tree Learning Algorithm"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2021-12-13T00:45:53.546461+00:00"}