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  • 标题:Predictive Analytics in Malaysian Dengue Data from 2010 until 2015 using BigML
  • 本地全文:下载
  • 作者:Zanariah Zainudin ; Siti Mariyam Shamsuddin
  • 期刊名称:International Journal of Advances in Soft Computing and Its Applications
  • 印刷版ISSN:2074-8523
  • 出版年度:2016
  • 卷号:8
  • 期号:3
  • 出版社:International Center for Scientific Research and Studies
  • 摘要:When era big data has reached to Malaysia, our governmentrealized that all data are streaming all over the Internet fromvarious data sources like sensors, social media data, excelspreadsheets, reviews, customer data, and etc. There are a lot datafrom our government need to be analysis which is can help decisionmaking in the future. This Malaysia Open data can be analysis tohelp the government to predict what the next planning to do. In thispaper, we use the Malaysia Open Data Government Portal aboutMalaysian Dengue Hotspot from 2010 until 2015. In the days,machine learning algorithms and technologies were mostly used byscientists, tech geeks or domain experts. However, severalorganizations are now using machine learning online and offlinetool to make these technologies available to the masses to peopleoutside. Online and offline tool make it easy for developers to applymachine learning to a dataset so as to add predictive features totheir applications. In this paper, we used BigML which it provideonline platform to integrate machine learning in real worldapplications and to predict the most popular place for Dengue to getan early warning and awareness to the people. BigML use thedecision tree algorithms to do data analytics and prediction thepopular place. In this case, we are using BigML to predict the placewhich always dengue occur in Malaysia which is also called ashotspot
  • 关键词:Malaysian Dengue Hotspot; Predictive Analytics; BigML
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