Machine Learning Methods to Classify Mushrooms for Edibility-A Review

There are thousands of species of Mushrooms in the world; they are edible and non-edible beingpoisonous. It is difficult for non-expertise person to Identify poisonous and edible mushroom of all the speciesmanually. So a computer aided system with software or algorithm is required to classify poisonous andnonpoisonous mushrooms. In this paper a literature review is presented on classification of poisonous andnonpoisonous mushrooms. Most of the research works to classify the type of mushroom have applied,machine learning techniques like Naïve Bayes, K-Neural Network, Support vector Machine(SVM), ArtificialNeural Network(ANN), Decision Tree techniques. In this literature review, a summary and comparisons of alldifferent techniques of mushroom classification in terms of its performance parameters, merits and demeritsfaced during the classification of mushrooms using machine learning techniques.