What is K-Nearest Neighbor Algorithm(KNN)? | KNN Classification Introduction - Part - 1

Описание: In this video on "What is K-Nearest Neighbor Algorithm (KNN)? | KNN Classification Introduction," we explain the basics of the KNN algorithm, a simple yet powerful machine learning technique used for classification and regression tasks. Learn how KNN makes predictions based on the proximity of data points and why it's popular for pattern recognition.

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This video on "What is K-Nearest Neighbor Algorithm (KNN)? | KNN Classification Introduction" includes the following topics:

00:00 Introduction
00:13 What is KNN?
00:52 Why KNN is Used in Machine Learning?
01:28 How KNN Works?
02:08 When to Use KNN?
02:32 Conclusion

What is the K-Nearest Neighbor (KNN) algorithm?
KNN is a supervised learning algorithm used for classification and regression. It classifies new data points based on the majority class among its nearest neighbors. The algorithm is non-parametric, meaning it makes no assumptions about the data distribution.

How does KNN work in classification tasks?
KNN calculates the distance between a new data point and all existing points, selecting the ‘K’ nearest neighbors. The new point is then classified based on the majority label among these neighbors, making KNN effective for pattern recognition and anomaly detection.

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