Abstract
Mushroom is an important fungus which contains a good source of vitamin B and a large amount of protein when compared to all other vegetables. It helps to prevent cancer, useful in weight loss and increases the immunity power of human. On the other hand, some mushrooms are toxic and can prove dangerous if we eat them. Therefore, it is a prominent task to differentiate, the edible and poisonous mushrooms. This paper focuses on developing a method for classification of mushroom using its texture feature, which is based on the machine learning approach. The performance of the proposed approach is 76.6% by using SVM classifier, which is found better with respect to the other classifiers like KNN, Logistic Regression, Linear Discriminant, Decision Tree, and Ensemble classifiers.
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Maurya, P., Singh, N.P. (2020). Mushroom Classification Using Feature-Based Machine Learning Approach. In: Chaudhuri, B., Nakagawa, M., Khanna, P., Kumar, S. (eds) Proceedings of 3rd International Conference on Computer Vision and Image Processing. Advances in Intelligent Systems and Computing, vol 1022. Springer, Singapore. https://doi.org/10.1007/978-981-32-9088-4_17
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DOI: https://doi.org/10.1007/978-981-32-9088-4_17
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