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Prediction Model for a Student to Find Best Department of Undergraduate Admission

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dc.contributor.author Hasan, Md. Showal
dc.contributor.author Al-Amin, Md.
dc.contributor.author Taleb, Md. Abu
dc.date.accessioned 2020-12-28T07:56:45Z
dc.date.available 2020-12-28T07:56:45Z
dc.date.issued 2020-10-12
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/5468
dc.description.abstract Our research title is "Prediction model for a student to find best department of undergraduate admission". We have used SPSS statistical platform for storing data and we have use WEKA to find out best algorithm model for finding best outcome according to our data structure. We have selected KNN model for our project. Finally we have used python language to implement the project. In this study, originally implemented by using Bangladeshi students' & educated employed students' real data. The data has learned to a machine using python language which is helped us to find out departments' successor prediction in percent serially. In this system, it has focused on previous group & group courses' result first. Moreover it is focused on general courses which process the overall result & match with the learned result which priority is the best profession & success too. As we know Bangladeshi students are too much brilliant. So, we think if they get the opportunity to choose which department is best for him and then it will be helpful for their career. en_US
dc.language.iso en en_US
dc.publisher Daffodil International University en_US
dc.subject Undergraduates en_US
dc.title Prediction Model for a Student to Find Best Department of Undergraduate Admission en_US
dc.type Other en_US


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