KNN method for different values of K on a handwritten digit data set

1. How does KNN algorithm set the value of K?
2. Can KNN be used when there are multiple predictor variables?
3. What are the different types of KNN algorithms?
4. How does handwritten digit recognition work?

How does KNN algorithm set the value of K?

The optimal K value usually found is the square root of N, where N is the total number of samples. Use an error plot or accuracy plot to find the most favorable K value. KNN performs well with multi-label classes, but you must be aware of the outliers.

Can KNN be used when there are multiple predictor variables?

As in KNN classification, we can use multiple predictors in KNN regression.

What are the different types of KNN algorithms?

With the help of KNN algorithms, we can classify a potential voter into various classes like “Will Vote”, “Will not Vote”, “Will Vote to Party 'Congress', “Will Vote to Party 'BJP'. Other areas in which KNN algorithm can be used are Speech Recognition, Handwriting Detection, Image Recognition and Video Recognition.

How does handwritten digit recognition work?

Handwritten digit recognition is the ability of a computer to recognize the human handwritten digits from different sources like images, papers, touch screens, etc, and classify them into 10 predefined classes (0-9). This has been a topic of boundless-research in the field of deep learning.