{"_buckets": {"deposit": "56f3c651-1ae7-443f-b112-23d66c94f8eb"}, "_deposit": {"id": "4354", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "4354"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/4354", "sets": ["1597824304333", "user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Feature Selection and Map Reduce-based Neural Network Classification for Big Data", "subitem_1551255648112": "en_US"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Nowadays, a large amount of digital data isgenerated from everywhere, every second of the day.One of the challenges is the volume of generated datawith high dimensionality. Most of traditional machinelearning algorithms are not good in training time andclassification result to find hidden insights from thesehigh dimensional data. Back-propagation NeuralNetwork, one of the most popular Artificial NeuralNetworks, is widely used in many classificationapplications. To reduce the data dimension, featureselection is needed to consider. MapReduce is asoftware framework for writing applications whichare run on Hadoop that supports rapid computationand processing of Big Data. In this paper, first thedimension of data is reduced using Chi-squaremethod. Then, Backpropagation Neural Network withMapReduce paradigm is used for classification.MapReduce-based Neural Network classifier isconstructed using one and two hidden layers. Sixdifferent datasets are used as case study and theperformance measures involve the training time,accuracy and number of selected features. Theresults of MapReduce-based Neural Networkalgorithm training on complete features and featuresselected subset are compared with WEKA tool andConventional Back-propagation Neural Network.Based on the experimental results, MapReduce-basedNeural Network algorithm give the superiorefficiency in training time and accuracy with reducednumber of features selected."}]}, "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": "2019-10-15"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "NJPSC 2019 Proceedings-pages-37-43.pdf", "filesize": [{"value": "1069 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 1069000.0, "url": {"url": "https://meral.edu.mm/record/4354/files/NJPSC 2019 Proceedings-pages-37-43.pdf"}, "version_id": "3d4ac053-a2d8-4135-a330-bf2078cce12b"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "University of Computer Studies, Yangon", "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": "Shine, Chit Thu"}, {"subitem_authors_fullname": "Nyunt, Thi Thi Soe"}]}]}, "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": "2019-03"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/2293"}, "item_title": "Feature Selection and Map Reduce-based Neural Network Classification for Big Data", "item_type_id": "21", "owner": "1", "path": ["1597824304333"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000004354", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-10-15"}, "publish_date": "2019-10-15", "publish_status": "0", "recid": "4354", "relation": {}, "relation_version_is_last": true, "title": ["Feature Selection and Map Reduce-based Neural Network Classification for Big Data"], "weko_shared_id": -1}