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"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

• Kasarapu Ramani

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.

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

"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