Edible and Poisonous Mushrooms Classification by Machine Learning Algorithms | Python IEEE Project
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Edible and Poisonous Mushrooms Classification by Machine Learning Algorithms | Python IEEE Project
2 511 просмотров · 3 г. назад
JP INFOTECH PROJECTS
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2 511 просмотров · 3 г. назад
Edible and Poisonous Mushrooms Classification by Machine Learning Algorithms | Python Final Year IEEE Project.
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🔗Email: jpinfotechprojects@gmail.com,
🌐Website: https://www.jpinfotech.org
📌Project Title: Edible and Poisonous Mushrooms Classification by Machine Learning Algorithms.
💡Implementation Code: Python.
🔬Algorithm / Model Used: Decision Tree Classifier.
🌐Web Framework: Flask.
🖥️Frontend: HTML, CSS, JavaScript.
💰Cost (In Indian Rupees): Rs.3000/.
📘Project Abstract:
👉The project "Edible and Poisonous Mushrooms Classification by Machine Learning Algorithms" endeavors to develop a machine learning-based system that can effectively differentiate between edible and poisonous mushrooms using 22 features in the Mushroom dataset.
👉The proposed model for classification is the Decision Tree Classifier, which has shown to be a promising algorithm for such classification tasks.
👉The performance evaluation is based on the training and testing accuracy of the Decision Tree Classifier. The results show that the proposed model achieves a 100% training and testing accuracy, which suggests its superiority over the existing system model AdaBoost.
📌REFERENCE:
Kemal Tutuncu; Ilkay Cinar; Ramazan Kursun; Murat Koklu, “Edible and Poisonous Mushrooms Classification by Machine Learning Algorithms”, 2022 11th Mediterranean Conference on Embedded Computing (MECO), IEEE Conference 2022.
🏷️tags:
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#mushroom #predictions