Integrating ontology with dataminig with a case of mushroom analysis

Authors

  • Maniraj V Associate professor, computer science, A.v.v.m sri pushpam college, poondi
  • Nithya J Computer science, A.v.v.m sri pushpam college, poondi

Keywords:

ONTOLOGY, MUSHROOM ANALYSIS, Data mining

Abstract

Data mining is extract the knowledge/information from a large amount of data which stores in multiple heterogeneous database. Data mining provides various techniques. Here using machine learning algorithm such as Pre- process, Classifier, Cluster and Association rule for help to improve the Predictive accuracy. Here presently the real data in the Explorer window for Exploring a data and applied these techniques to real mushroom data for predicting a edible mushrooms. They are described in terms of physical characteristics. The mushroom dataset can be based it’s attributes. All of the attribute values were nominal. Each field has a set of letter as possible values. It consists of a set of records with 22 attributes and a class label, Poisonous (or) Edible. The classifier could very well be a safe way to determine which Mushrooms I can and I can’t Eat. Then considering clustering algorithm with some enhancements to aid in the process of identification of Mushroom characteristics. To applied a classify techniques for predicting a correctly classified and incorrectly classified instances. Association rule mainly used for finding the best rule. In this rule is used to making decision for identify the mushroom is edible or poisonous.

References

Mushroom records drawn from The Audubon Society Field Guide to North American Mushrooms (1981). G. H. Lincoff (Pres.), New York: Alfred A. Knopf

Artificial Intelligence: A Modern Approach, 3rd edition (blue) Stuart J. Russell and Peter Norvig. Prentice Hall, Englewook Cliffs, N.J., 2010, 702.

Mushroom Poisoning: http://en.wikipedia.org/wiki/Mushroom_poisoning

Mushroom Database: https://courses.cs.washington.edu/courses/cse473/01au/Assignments/mushroom-names.txt

―G EFFECTIVE USE OF THE KDD PROCESS AND DATA MINING FOR COMPUTER PERFORMANCE PROFESSIONALS ― by Susan P. Imberman Ph.D. College of Staten Island, City University of New York

―DATA MINING TECHNIQUES CLASSIFICATION AND PREDICTION ―by Han/Kamber/Pei,Tan/Steinbach/Kumar, and Andrew MooreMirekRiedewald

c―CLASSIFICATION AND PREDICTION IN A DATA MINING APPLICATION ― by SERHAT ÖZEKES and A.YILMAZ ÇAMURCU 2 Istanbul

Commerce University, Ragıp Gümüş pala Cad. No: 84 Eminönü 34378, Istanbul –Turkey

―SURVEY OF CLASSIFICATION TECHNIQUES IN DATA MINING ― byThair NuPhyu E. H. Miller, ―A note on reflector arrays (Periodical

style—Accepted for publication),‖ IEEE Trans. Antennas Propagat., to be published.

DATA MINING TECHNOLOGY by Jiawei Han Department of Computer Science University of Illinois at Urbana-Champaign

Mushroom Poisoning: http://en.wikipedia.org/wiki/Mushroom_poisoning.

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Published

2024-02-26

How to Cite

Maniraj, V., & Nithya, J. (2024). Integrating ontology with dataminig with a case of mushroom analysis. COMPUSOFT: An International Journal of Advanced Computer Technology, 4(10), 1983–1988. Retrieved from https://ijact.in/index.php/j/article/view/348

Issue

Section

Original Research Article

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