Classification Model of Prediction for Placement of Students

نویسنده

  • Ajay Kumar Pal
چکیده

Data mining methodology can analyze relevant information results and produce different perspectives to understand more about the students’ activities. When designing an educational environment, applying data mining techniques discovers useful information that can be used in formative evaluation to assist educators establish a pedagogical basis for taking important decisions. Mining in education environment is called Educational Data Mining. Educational Data Mining is concerned with developing new methods to discover knowledge from educational database and can used for decision making in educational system. In this study, we collected the student’s data that have different information about their previous and current academics records and then apply different classification algorithm using Data Mining tools (WEKA) for analysis the student’s academics performance for Training and placement. This study presents a proposed model based on classification approach to find an enhanced evaluation method for predicting the placement for students. This model can determine the relations between academic achievement of students and their placement in campus selection.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

S3PSO: Students’ Performance Prediction Based on Particle Swarm Optimization

Nowadays, new methods are required to take advantage of the rich and extensive gold mine of data given the vast content of data particularly created by educational systems. Data mining algorithms have been used in educational systems especially e-learning systems due to the broad usage of these systems. Providing a model to predict final student results in educational course is a reason for usi...

متن کامل

A Hybrid Business Success Versus Failure Classification Prediction Model: A Case of Iranian Accelerated Start-ups

The purpose of this study is to reduce the uncertainty of early stage startups success prediction and filling the gap of previous studies in the field, by identifying and evaluating the success variables and developing a novel business success failure (S/F) data mining classification prediction model for Iranian start-ups. For this purpose, the paper is seeking to extend Bill Gross and Robert L...

متن کامل

The Mediating Role of Placement in Service Quality of Education: From International Students’ Perspective

The drive of this investigation is to diagnose the mediation effect of placement between program quality, industrial link, student satisfaction, and service quality in the circumstance of tertiary education in Malaysia. Using the Cue Utilization theory, the proposed model is tested employing data collected from 173 international students who are pursuing study at University Utara Malaysia throu...

متن کامل

A Validation Test Naive Bayesian Classification Algorithm and Probit Regression as Prediction Models for Managerial Overconfidence in Iran's Capital Market

Corporate directors are influenced by overconfidence, which is one of the personality traits of individuals; it may take irrational decisions that will have a significant impact on the company's performance in the long run. The purpose of this paper is to validate and compare the Naive Bayesian Classification algorithm and probit regression in the prediction of Management's overconfident at pre...

متن کامل

Prediction model of limestone rock mass quality, using seismic wave velocity (Case study: Sarvak formation in Bakhtiari dam site)

The purpose of this study was to develop a model for the estimation of rock mass classification of Sarvak limestone in the Bakhtiari dam site, south-west (SW) Iran. Q system had been used as the starting point for the rock mass classification. This method was modified for sedimentary rock mass which is known as Qsrm. Because Qsrm considers a wide range of rock mass propert...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2013