Study of Online Pre-admission Enquiry Prediction under the Framework of k-Nearest Neighbor (k-NN) Algorithm
Authors
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Department of Computer Science and Technology, Swami Vivekananda University, Barrackpore, West Bengal, India. ,IN
Bidyut Roy -
Department of Computer Science and Technology, Swami Vivekananda University, Barrackpore, West Bengal, India. ,INBablu Pramanik
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Department of Computer Science and Technology, Swami Vivekananda University, Barrackpore, West Bengal, India. ,INManoj Kumar Srivastav
DOI:
https://doi.org/10.18311/jmmf/2023/34165Keywords:
Enquiry, Admission, K-NN, Predict.Abstract
Admission to an appropriate college is an important process. The method of enquiry is an important part of it. As a result, students gather data, analyse it, and attempt to predict which college is best for them to attend. In general, students find it useful to research the trends in fee structures, academic staff numbers, multi-national companies tie up, and placements received by students during that academic year. K-Nearest Neighbors (k-NN) is one of the simplest learning algorithms used in supervised learning approaches. It makes assumptions about the similarity between new cases or data and available cases and places new cases in the category that most closely resembles the available categories. In this paper, the authors have tried to identify or predict the category or class of a particular dataset using the k-NN algorithm.
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