Applications of Machine Learning Techniques in the Classification of Mushrooms

Millions of different species of mushrooms are thought to exist today. Two main categories of mushrooms exist namely eatable and hazardous mushrooms. Since many individuals are unaware that mushrooms are harmful, they frequently contract food poisoning. There have been incidences of poisoning from poisonous mushrooms recorded even in some other nations. However, due to the abundance of mushrooms and their comparison-based qualities, it might be difficult to categorize them among edible and dangerous mushrooms. For the identification of the variety of mushrooms, precise classification helps to discover crucial forms, from many numbers of records of data. The technique used to categorize the categories of mushrooms using logistic regression, linear regression, support vector classifier, k-nearest neighbors, random forest, and gradient boosting. Among all the methods the random forest shows the greatest accuracy rate.