IJFANS International Journal of Food and Nutritional Sciences

ISSN PRINT 2319 1775 Online 2320-7876

TO COMPARE THE DECISION TREE AND RANDOM FOREST ALGORITHM IN CATEGORIZING LEARNERS OF THE NAVI MUMBAI REGION

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Ms. Nutan Sawant

Abstract

With an increasing number of learners in the institute, it will be very difficult to correctly divide them into different categories based on their capabilities and provide them with perfect pedagogy as per their needs. To provide a smart teaching-learning process, we can categorize the learners at the beginning of the academic year based on their performance in preliminary tests. It can be categorized based on the learner’s grasping skills as slow, less advanced, and advanced learners. We can use artificial intelligence techniques to assist the institute in the classification of learners in an intelligent manner. Different Classification Algorithms of Machine Learning can be used to split the learners into different predefined classes. Based on learners’ performance in the preliminary assessments, we can provide them with additional online courses along with their regular curriculum to improve their learning.

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