Publication:
A study on using Python vs Weka on dialysis data analysis

dc.contributor.authorJarernsri Mitrpanonten_US
dc.contributor.authorWudhichart Sawangpholen_US
dc.contributor.authorThanita Vithantirawaten_US
dc.contributor.authorSinattaya Paengkaewen_US
dc.contributor.authorPrameyuda Suwannasingen_US
dc.contributor.authorAtthapan Daramasen_US
dc.contributor.authorYi Cheng Chenen_US
dc.contributor.otherNational Central University Taiwanen_US
dc.contributor.otherMahidol Universityen_US
dc.date.accessioned2019-08-23T10:57:58Z
dc.date.available2019-08-23T10:57:58Z
dc.date.issued2018-01-12en_US
dc.description.abstract© 2017 IEEE. Health data has been drastically increasing in capacity and variety. Due to large and complex collection of datasets, it is difficult to process data using traditional data processing techniques. Machine Learning techniques, such as KNN and Naïve Bayes, have been used. Python and Weka are tools that are widely used in the field of data analytics. Therefore, this paper gives the comprehensive comparison between both tools together with some machine learning algorithms on data analytic of Dialysis Dataset. The results show that using Python provides the better performance in term of correct/incorrect instances, precision, and recall.en_US
dc.identifier.citationProceeding of 2017 2nd International Conference on Information Technology, INCIT 2017. Vol.2018-January, (2018), 1-6en_US
dc.identifier.doi10.1109/INCIT.2017.8257883en_US
dc.identifier.other2-s2.0-85049463756en_US
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/20.500.14594/45655
dc.rightsMahidol Universityen_US
dc.rights.holderSCOPUSen_US
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85049463756&origin=inwarden_US
dc.subjectComputer Scienceen_US
dc.titleA study on using Python vs Weka on dialysis data analysisen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85049463756&origin=inwarden_US

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