A Review on Analysis of K-Nearest Neighbor Classification Machine Learning Algorithms based on Supervised Learning

A Review on Analysis of K-Nearest Neighbor Classification Machine Learning Algorithms based on Supervised Learning
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© 2022 by IJETT Journal
Volume-70 Issue-7
Year of Publication : 2022
Authors : Manish Suyal, Parul Goyal
DOI : 10.14445/22315381/IJETT-V70I7P205

How to Cite?

Manish Suyal, Parul Goyal, "A Review on Analysis of K-Nearest Neighbor Classification Machine Learning Algorithms based on Supervised Learning" International Journal of Engineering Trends and Technology, vol. 70, no. 7, pp. 43-48, 2022. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I7P205

Abstract
Machine learning is a small part of artificial intelligence. Machine learning is one of the most trending technologies in the world today. Whatever you search on Google, Google takes your data and uses machine learning to show your advertisement and search results accordingly. In the same way the type of video you watch on YouTube, YouTube also recommends the same type of video to you. A machine learning system works on the principle that it has to take input data, learn something from it, and give output. In machine learning, a machine learning computer program is trained by giving input data, and output is produced based on that input data. The paper aims to determine how the K-Nearest Neighbor (KNN) machine learning classification algorithm is applied to the model dataset and how the given data is predicted by the model to which class this given data will exist. K-Nearest Neighbor (KNN) is the simplest machine learning algorithm based on supervised learning. The K-NN algorithm is mostly used in solving the classification problem. Supervised learning is a type of machine learning algorithm. In supervised learning, input and output data are already provided to the machine, so the training data is also called labeled data. When a new input is given to the machine, it will give the output only according to its previous experience and data.

Keywords
Artificial Intelligence, K-Nearest Neighbor (KNN) Classification Algorithm, Machine learning, Supervised Learning Algorithm, K-Nearest Neighbor (KNN) Classification Algorithm, Labeled Data.

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