K-Nearest Neighbor algorithm (KNN)

Working principle:

Classification algorithm.

When a new unlabeled sample is entered, the algorithm extracts the K-category labels for the nearest neighbor of the sample in the training sample set and the samples to be sorted (for example, there are only two characteristics of the sample, the point in the two-dimensional coordinate system is used to represent a sample, and the nearest K-point is selected from the new sample point). Select the category with the most occurrences of the K category labels as the classification for the new data.

K-Nearest Neighbor algorithm (KNN)