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A Comparative Study on Mushroom Classification using Supervised Machine Learning Algorithms

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A Comparative Study on Mushroom Classification using Supervised Machine Learning Algorithms


Kanchi Tank



Kanchi Tank "A Comparative Study on Mushroom Classification using Supervised Machine Learning Algorithms" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5, August 2021, pp.716-723, URL: https://www.ijtsrd.com/papers/ijtsrd42441.pdf

Mushroom hunting is gaining popularity as a leisure activity for the last couple of years. Modern studies suggest that some mushrooms can be useful to treat anemia, improve body immunity, fight diabetes and a few are even effective to treat cancer. But not all the mushrooms prove to be beneficial. Some mushrooms are poisonous as well and consumption of these may result in severe illnesses in humans and can even cause death. This study aims to examine the data and build different supervised machine learning models that will detect if the mushroom is edible or poisonous. Principal Component Analysis (PCA) algorithm is used to select the best features from the dataset. Different classifiers like Logistic Regression, Decision Tree, K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Naïve Bayes and Random Forest are applied on the dataset of UCI to classify the mushrooms as edible or poisonous. The performance of the algorithms is compared using Receiver Operating Characteristic (ROC) Curve.

Mushroom Classification, Principal Component Analysis, Logistic Regression, Decision Tree, K-Nearest Neighbor, Support Vector Machine, Naïve Bayes, Random Forest


IJTSRD42441
Volume-5 | Issue-5, August 2021
716-723
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

International Journal of Trend in Scientific Research and Development - IJTSRD having online ISSN 2456-6470. IJTSRD is a leading Open Access, Peer-Reviewed International Journal which provides rapid publication of your research articles and aims to promote the theory and practice along with knowledge sharing between researchers, developers, engineers, students, and practitioners working in and around the world in many areas like Sciences, Technology, Innovation, Engineering, Agriculture, Management and many more and it is recommended by all Universities, review articles and short communications in all subjects. IJTSRD running an International Journal who are proving quality publication of peer reviewed and refereed international journals from diverse fields that emphasizes new research, development and their applications. IJTSRD provides an online access to exchange your research work, technical notes & surveying results among professionals throughout the world in e-journals. IJTSRD is a fastest growing and dynamic professional organization. The aim of this organization is to provide access not only to world class research resources, but through its professionals aim to bring in a significant transformation in the real of open access journals and online publishing.

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