Title: A survey of factors influencing on admission in SAMPAD schools with data mining methods

Authors: Nabi-Allah Yoosefi-Gorji; Mansour Esmaeilpour

Addresses: Management Information Technology Department, Hamedan Branch, Islamic Azad University, Hamedan, Iran ' Computer Engineering Department, Hamedan Branch, Islamic Azad University, Hamedan, Iran

Abstract: Admission in SAMPAD schools is a significant milestone for students and their parents in Iran. This paper is a survey of factors influence on admission in the SAMPAD schools. It was made with data mining methods using a case study approach in Mazandaran province education in Iran for educational year 2013 to 2014. We collect data from 1999 students, who applied for these schools in addition, and have a statistical overview on quality and quantity of data in various groups of students. Furthermore, a detailed analysis with data mining conceptions is made on data and the patterns hid in them are determined. For this purpose, at first we pre-process data and train the network with naïve-base algorithm and multilayer perceptron. Then, we calculate the accuracy of the model and the work continues with rough set and decision tree algorithms. Finally, we derive the best rules from combining all these methods.

Keywords: data mining; naïve-base algorithm; multilayer perceptron; MLP; artificial neural network; ANN; rough set theory; decision tree algorithm; SAMPAD schools in Iran.

DOI: 10.1504/IJAPR.2017.085309

International Journal of Applied Pattern Recognition, 2017 Vol.4 No.2, pp.181 - 205

Received: 01 Jul 2016
Accepted: 30 Oct 2016
Published online: 21 Jul 2017 *

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