Classification Algorithms for Mushroom Identification

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Published Dec 23, 2021

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Sena Goral
Mehmet Akif Ersoy University, Turkey

Abstract

When examined around the world, it was determined that there are many types of mushrooms. Mushrooms are among the important nutrients for human life in many respects. An important feature of mushrooms used in various researches is that they are edible or poisonous. Different types of mushrooms have many characteristics. These features can be common in different features. However, the poisonousness of the mushroom can be determined by examining many features. In this study, whether the mushrooms are poisonous or edible is examined. In this study, 5 different classification methods were used. These; Logistic Regression, KNeigborsClassifier, DecisionTreeClassifier, RandomForestClassifier, and SVM. As a result, it was determined that SVM was the method that gave the most accurate result in this study.

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How to Cite
GORAL, Sena. Classification Algorithms for Mushroom Identification. Journal of Multidisciplinary Developments, [S.l.], v. 6, n. 1, p. 90-96, dec. 2021. ISSN 2564-6095. Available at: <http://jomude.com/index.php/jomude/article/view/98>. Date accessed: 12 dec. 2024.
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Issue
Vol 6 No 1 (2021): "New Era": Volume: 6, Issue: 1
Section
Natural Sciences - Regular Research Paper

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References

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