Analysis of Improved ID3 Algorithm using Havrda & Charvat Entropy

Authors(2) :-Kirandeep, Prof. Neena Madan

Data mining is often called as knowledge discovery procedure. We use data mining techniques in order to identify the patterns and relationships among them. Data mining consist of combinations of Machine learning, Visualization for identifying the patterns. Data mining consist of different techniques which can be used to complete a goal. From all the data we need to find the data which will give more information which will help to predict the performance. Data mining techniques allows us to discover hidden patterns, relationship form huge amount of data. Information extracted from large database is helpful in decision making. By referring the extracted information the processing methodologies are selected. The objective of data mining is to identify valid, novel, potentially useful, and understandable correlations and patterns in existing data. Finding useful patterns in data is known by different names (e.g., knowledge extraction, information discovery, information harvesting, data archeology, and data pattern processing)

Authors and Affiliations

Kirandeep
Guru Nanak Dev University Regional Campus, Jalandhar In Partial Fulfillment For Degree Of Master's In Computer Science & Engineering, Jalandhar, Punjab, India
Prof. Neena Madan
Guru Nanak Dev University Regional Campus, Jalandhar In Partial Fulfillment For Degree Of Master's In Computer Science & Engineering, Jalandhar, Punjab, India

ID3,Improved ID3,Havrda & Charvat entropy

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Publication Details

Published in : Volume 3 | Issue 3 | March-April 2018
Date of Publication : 2018-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 08-13
Manuscript Number : CSEIT18339
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Kirandeep, Prof. Neena Madan, "Analysis of Improved ID3 Algorithm using Havrda & Charvat Entropy", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 3, pp.08-13, March-April-2018.
Journal URL : http://ijsrcseit.com/CSEIT18339

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