%0 Journal Article %1 noauthororeditor %A Madan, Kirandeep Prof. Neena %D 2018 %J International Journal of Trend in Scientific Research and Development %K Computer Decisions Engineering algorithm techniquesID3 treeClassification %N 3 %P 740-744 %T Deployment of ID3 decision tree algorithm for placement prediction %U http://www.ijtsrd.com/engineering/computer-engineering/11073/deployment-of-id3-decision-tree-algorithm-for-placement-prediction/kirandeep %V 2 %X 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. 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

@article{noauthororeditor, abstract = {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. 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 }, added-at = {2018-09-04T08:23:39.000+0200}, author = {Madan, Kirandeep Prof. Neena}, biburl = {https://www.bibsonomy.org/bibtex/2a68f5dd673275ca5ec888b119c94f8ef/ijtsrd}, interhash = {44e0d1cc62af9283e68d380de1530c5e}, intrahash = {a68f5dd673275ca5ec888b119c94f8ef}, issn = {2456-6470}, journal = {International Journal of Trend in Scientific Research and Development}, keywords = {Computer Decisions Engineering algorithm techniquesID3 treeClassification}, language = {English}, month = {April}, number = 3, pages = {740-744}, timestamp = {2018-10-02T11:01:27.000+0200}, title = {Deployment of ID3 decision tree algorithm for placement prediction }, url = {http://www.ijtsrd.com/engineering/computer-engineering/11073/deployment-of-id3-decision-tree-algorithm-for-placement-prediction/kirandeep}, volume = 2, year = 2018 }