Generating Licensure Examination Performance Models Using PART and JRip Classifiers: A Data Mining Application in Education

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Provided by: International Association of Computer Science & Information Technology (IACSIT)
Topic: Big Data
Format: PDF
In this paper the authors focused on the generation of the licensure examination performance models implementing PART and JRip classifiers. Specifically, it identified the attributes that are significant to the response attribute; it generated prediction models using the PART and JRip classifiers of WEKA; and it determined how likely is reviewed to pass the LET. The respondents were obtained from the education graduates of Isabela State University Cabagan campus who took a LET review and eventually took the September 2013 LET.
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