{"_buckets": {"deposit": "b7717982-df9e-44cd-a613-bbe3559c80b9"}, "_deposit": {"id": "4554", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "4554"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/4554", "sets": ["1597824322519", "user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Comparison of Data Mining Classification Algorithms: C5.0 and CART for Car Evaluation and Credit Card Information Datasets", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Big data and its analysis have become a widespread practice in recent times,applicable to multiple industries. Data mining is a technique that is based on statisticalapplications. It is the process of discovering hidden or unknown patterns in hugedatasets that are potentially useful and ultimately understandable. The goal of datamining is to extract useful information from huge data sets and to store it as anunderstandable and structured model for future use, using combined technique ofstatistics, machine learning and database systems. Classification is a supervisedmethod, which is used to predict categorical class label of a given data instance so asto classify it into a predetermined class. Decision tree is the simple and mostcommonly used algorithm among the classification algorithms. This system analysesthe performance of CART and C5.0 algorithms based on training and testing phasesfor two UCI datasets: car evaluation and credit card datasets using evaluation metricssuch as accuracy, processing time and decision rules. It is a two-step process, in thefirst step, algorithm uses training data to build a classifier, and then in second step ituses this classifier to estimate the class label of data instance. The classifier is like afunction that maps a data instance to a label. The system aims to compare the resultsof both algorithms and discovers in which either one of them is significantlyoutperforming the other.This system implemented using C# programing language with MicrosoftVisual Studio 2013 and Microsoft SQL Server Management Studio 2012 platform tobuild the database."}]}, "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": "2020-01-22"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "5MCS-33 Ei Thinzar Win Maung.pdf", "filesize": [{"value": "4213 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 4213000.0, "url": {"url": "https://meral.edu.mm/record/4554/files/5MCS-33 Ei Thinzar Win Maung.pdf"}, "version_id": "d54d9f60-f189-4ca3-8cd7-2360d53b248a"}]}, "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": "Unversity of Computer Studies, Yangon", "subitem_supervisor(s)": [{"subitem_supervisor": ""}]}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Maung, Ei Thinzar Win"}]}]}, "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": "2020-01"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/2476"}, "item_title": "Comparison of Data Mining Classification Algorithms: C5.0 and CART for Car Evaluation and Credit Card Information Datasets", "item_type_id": "21", "owner": "1", "path": ["1597824322519"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000004554", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2020-01-22"}, "publish_date": "2020-01-22", "publish_status": "0", "recid": "4554", "relation": {}, "relation_version_is_last": true, "title": ["Comparison of Data Mining Classification Algorithms: C5.0 and CART for Car Evaluation and Credit Card Information Datasets"], "weko_shared_id": -1}