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Published in:

Volume 5 Issue 1
January-2018
eISSN: 2349-5162

Unique Identifier

JETIR1801122

Page Number

639-642

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Title

Machine Learning Tools for Dataset Classification

ISSN

2349-5162

Cite This Article

"Machine Learning Tools for Dataset Classification", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 1, page no.639-642, January-2018, Available :http://www.jetir.org/papers/JETIR1801122.pdf

Authors

Abstract

Mushrooms, as a kind of food, are very special due to their edibility. Some countries treat mushrooms as a kind of high nutrition food. Still, only tiny portions of them are edible. It is really toxic to consume a poisonous mushroom. Thus, we used Decision Tree and Naïve Bayes classification algorithms to develop a best model to classify mushrooms that are edible based on the detected data of the mushrooms. Also the performance of these classification algorithms is tested on two different tools such as Weka and Spark. The performance is expressed in terms of parameters correctly classified instances, incorrectly classified instances, errorrate and precision. The Decision Tree algorithm has outperformed with respect to Weka tool while the Naïve Bayes algorithm outperformed in the Spark.

Key Words

Machine Learning, Classification, Decision Tree, Naïve Bayes, Mushroom Classification

Cite This Article

"Machine Learning Tools for Dataset Classification", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 1, page no. pp639-642, January-2018, Available at : http://www.jetir.org/papers/JETIR1801122.pdf

Publication Details

Published Paper ID: JETIR1801122
Registration ID: 180141
Published In: Volume 5 | Issue 1 | Year January-2018
DOI (Digital Object Identifier):
Page No: 639-642
ISSN Number: 2349-5162

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Cite This Article

"Machine Learning Tools for Dataset Classification", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 1, page no. pp639-642, January-2018, Available at : http://www.jetir.org/papers/JETIR1801122.pdf




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