{"created":"2020-09-01T14:15:30.473251+00:00","id":4163,"links":{},"metadata":{"_buckets":{"deposit":"149fd27e-1eba-4d39-894f-61047a467b35"},"_deposit":{"id":"4163","owners":[],"pid":{"revision_id":0,"type":"recid","value":"4163"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/4163","sets":["1582963302567:1597824273898"]},"communities":["ucsy"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"Classification of Water Pollution with Feature Selection","subitem_1551255648112":"en"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"In the feature subset selection problem, alearning algorithm is faced with the problem ofselecting a relevant subset of features upon which tofocus its attention to achieve the highest predictiveaccuracy with the learning algorithm on thisdomain, a feature subset selection method shouldconsider how the algorithm and the training datainteract with filter method. This paper applies thenormalization by decimal scaling process beforefeature selection to speed up the learning phase andprevent attributes with initially smaller ranges. Thispaper uses sequential forward selection to improvethe generalization performance of patternrecognizers for water pollute or not. k-NearestNeighbor classifier is built with filter approach byusing the sequential forward selection. To estimatehow accurately a classifier labels future data, thispaper evaluates the performance of k-NearestNeighbor classifier on the complete features and theselected feature subset by using the k-fold crossvalidation."}]},"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":"2019-08-06"}],"displaytype":"preview","filename":"55307.pdf","filesize":[{"value":"426 Kb"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://meral.edu.mm/record/4163/files/55307.pdf"},"version_id":"fc9ee944-efb3-4357-834a-64c471ebe035"}]},"item_1583103131163":{"attribute_name":"Journal articles","attribute_value_mlt":[{"subitem_issue":"","subitem_journal_title":"Fourth 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":"Win, Pwint Mar Naing"},{"subitem_authors_fullname":"Aung, Thandar"}]}]},"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":"2009-12-30"},"item_1583159847033":{"attribute_name":"Identifier","attribute_value":"http://onlineresource.ucsy.edu.mm/handle/123456789/1860"},"item_title":"Classification of Water Pollution with Feature Selection","item_type_id":"21","owner":"1","path":["1597824273898"],"publish_date":"2019-08-06","publish_status":"0","recid":"4163","relation_version_is_last":true,"title":["Classification of Water Pollution with Feature Selection"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2021-12-13T01:28:59.606035+00:00"}