A Generalized Data mining Framework for Placement Chance Prediction Problems

Data Mining is such a promising technology whose worth becomes evident when it can be applied to a domain where a common man is benefited. This paper is an attempt to help the prospective students to make wise career decisions using technologies like data mining using decision trees, Naïve Bayes and...

Full description

Saved in:
Bibliographic Details
Published in:International journal of computer applications 2011-01, Vol.31 (3), p.40-47
Main Authors: Elayidom, Sudheep, Idikkula, Sumam Mary, Alexander, Joseph
Format: Article
Language:English
Subjects:
Categories
Computer simulation
Data mining
Decision trees
Entrances
Mathematical models
Placement
Students
Citations: Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Data Mining is such a promising technology whose worth becomes evident when it can be applied to a domain where a common man is benefited. This paper is an attempt to help the prospective students to make wise career decisions using technologies like data mining using decision trees, Naïve Bayes and artificial neural networks. A student enters his Entrance Rank, Gender (M/F), Sector (rural/urban) and Reservation category. Based on the entered information the Network or the decision tree will return which branch of study is Excellent, Good, Average or poor for him/her. Also in this paper we compare the performance of the models on the same data and propose a generalized data mining framework for problems of similar nature.
ISSN:0975-8887
0975-8887
DOI:10.5120/3807-5257