Python for Machine Learning - The Complete Beginners Course - K-Nearest Neighbors Algorithm

The video tutorial explains the concept of similarity between two classes using a visual example. It introduces the Kehne classifier, which assigns a new data point to a category based on the highest number of similar neighbors. The tutorial also covers the Euclidean distance formula, which is used to calculate the distance between two points and identify the nearest neighbor.

Describe the relationship between the categories A&B and the new data point in the context of similarity.

What is the basis on which the Kehne classifier assigns a new data point to a category?

Explain the significance of the number of neighbours in the classification process.

How does the Kehne classifier determine which category to assign to a new data point?

What is the Euclidean distance and how is it relevant to finding the nearest neighbour?