The classification of mushroom using ML | ||||
| Kafrelsheikh Journal of Information Sciences | ||||
| Volume 4, Issue 2, November 2023 PDF (761.21 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/kjis.2023.221370.1016 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Sara A shehab  1; Eman Shehab2; Rahma Nabil3
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| 1Computer Science Dep, Faculty of Computer and Artificial Intelligence, Sadat city, Egypt | ||||
| 2Department of computer science, faculty of computers and artificial intellgence, sadat city | ||||
| 3Student in Bioinformatic, faculty of computers and artificial intellgence, sadat city | ||||
| Abstract | ||||
| The Mushroom is kind of fungi. Major health benefits of mushrooms include their ability to kill cancer cells. The goal of this research is to determine the most effective method for mushroom classification, with the categories of deadly and nonpoisonous mushrooms being used. Separate from plants and animals, they belong in their own realm. In terms of how they get nutrients, fungi are different from plants and mammals. Mushrooms are classified as edible and poisoned. To distinguish between two varieties of mushrooms, we can use machine learning, which is used in classification. There are numerous machine learning algorithms that perform classification, but in our model, I utilize random forest, MLP, Linear Regression and decision tree on the features of the mushroom to categorize it into edible and poisonous. Random Forest achieves high accuracy 98.70%. from these results, we can use Ml to differentiate between two varieties of mushrooms because it is used in classification efficiently. | ||||
| Keywords | ||||
| Mushroom; fungi; Classification Machine Learning; Random Forest | ||||
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