Exploring hidden relationships within students' data using neural network and logistic regression

Considerable attention has been given to the development of sophisticated techniques for exploring data sets.One of the most commonly used techniques is neural networks that have the abilities to detect nonlinear effects and/or interactions.Due to the reduced interpretability of the output model of...

Full description

Saved in:
Bibliographic Details
Main Authors: Siraj, Fadzilah, Yusoff, Nooraini, Mohd Ali, Noorlin
Format: Book Section
Language:English
Published: Faculty of Information Technology, Universiti Utara Malaysia 2006
Subjects:
Online Access:http://repo.uum.edu.my/2386/1/Fadzillah_Siraj%2C_Nooraini_Yusoff_%282006%29_01.pdf
http://repo.uum.edu.my/2386/
http://lintas.uum.edu.my:8080/elmu/index.jsp?module=webopac-l&action=fullDisplayRetriever.jsp&szMaterialNo=0000242843
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Considerable attention has been given to the development of sophisticated techniques for exploring data sets.One of the most commonly used techniques is neural networks that have the abilities to detect nonlinear effects and/or interactions.Due to the reduced interpretability of the output model of neural networks the some data set has been analyzed using logistic regression.In this study both techniques have been applied to education data set.The study aims to provide some insight into fist year students undertaking undergraduate programs namely Bachelor of Information Technology (BIT),Bachelor of Multimedia (BMM) and Bachelor in Management of Technology (BMoT) at University Utara Malaysia. The Holland Personality Model was used to indicate the students personality traits in conjunction with students academic achievement of accuracies in both methods the methods were used in this exploratory study in a complementary manner.