Deployment of ID3 decision tree algorithm for placement prediction IJTSRD


This paper details the ID3 classification algorithm. Very simply, ID3 builds a decision tree from a fixed set of examples. The resulting tree is used to classify future samples. The decision node is an attribute test with each branch (to another decision tree) being a possible value of the attribute. ID3 uses information gain to help it decide which attribute goes into a decision node. The main aim of this paper is to identify relevant attributes based on quantitative and qualitative aspects of a student’s profile such as CGPA, academic performance, technical and communication skills and design a model which can predict the placement of a student. For this purpose ID3 classification technique based on decision tree has been used.

by Kirandeep | Prof. Neena Madan”Deployment of ID3 decision tree algorithm for placement prediction”

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018,

URL: http://www.ijtsrd.com/papers/ijtsrd11073.pdf

http://www.ijtsrd.com/engineering/computer-engineering/11073/deployment-of-id3-decision-tree-algorithm-for-placement-prediction/kirandeep

call for paper Agricultural Engineering, international journal Chemical Engineering, ugc approved journals for engineering


Deployment of ID3 decision tree algorithm for placement prediction IJTSRD


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