{"_buckets": {"deposit": "f5899f1d-4658-433e-96a1-bb8e55490c3f"}, "_deposit": {"id": "4312", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "4312"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/4312", "sets": ["1597824322519", "user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "The Comparison of Classification Methods on Software Defect Data Sets", "subitem_1551255648112": "en_US"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Nowadays, it is difficult for us to imagine a life without devices that iscontrolled by software. Software quality has become the main concern during thesoftware development. Software quality is a field of study and practice that describesthe desirable attributes of software products. Software quality prediction is a processof utilizing software metrics such as code-level measurements and defect data to buildclassification models that are able to estimate the quality of program modules. Themajor problem that affects the quality of datasets is high dimensionality and classimbalanced. A more useful and efficient mechanism is k Nearest Neighbor method,where Nearest Neighbor classify classes of testing dataset based on k nearest neighborof training dataset. Another mechanism is Class Based Weighted k Nearest Neighborwith BINER Algorithm for classifying classes of testing dataset. By using BINERAlgorithm, it narrows down the training dataset range instead of whole trainingdataset that has the maximum likelihood of occurrence and then CBW k-NN classifiesclasses of testing dataset based on this range. This thesis is the comparison of twoclassification methods by classifying classes of testing dataset focuses on NASAMDP (PC1, CM1 and JM1) datasets. The comparison results of two methods based onAccuracy, Reliability, Mean Absolute Error and Root Mean Squared Error."}]}, "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": "2019-09-23"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "HninYiSan.pdf", "filesize": [{"value": "2558 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 2558000.0, "url": {"url": "https://meral.edu.mm/record/4312/files/HninYiSan.pdf"}, "version_id": "afaa3fbe-fa5d-400c-a4ea-ae2cc140325d"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "", "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": "University of Computer Studies, Yangon", "subitem_supervisor(s)": [{"subitem_supervisor": ""}]}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "San, Hnin Yi"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Thesis"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2018-12"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/2251"}, "item_title": "The Comparison of Classification Methods on Software Defect Data Sets", "item_type_id": "21", "owner": "1", "path": ["1597824322519"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000004312", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-09-23"}, "publish_date": "2019-09-23", "publish_status": "0", "recid": "4312", "relation": {}, "relation_version_is_last": true, "title": ["The Comparison of Classification Methods on Software Defect Data Sets"], "weko_shared_id": -1}