Introduction to Machine Learning (11): Regression and clustering algorithms-unsupervised learning (K-means algorithm)

Learning Directory:

Content directory:

Unsupervised learning includes algorithms:

Clustering: K-means (K-means clustering)
dimensionality reduction: PCA

K-means principle

API：

Case:

How to evaluate unsupervised learning?

Summary of K-means algorithm:

Features : It uses an iterative algorithm, which is intuitive, easy to understand and practical.
Disadvantages : easy to converge to a local optimal solution (when k initial points are clustered together). Multiple clustering can be used to solve the
application scenario : when there is no target value, Do clustering first, then how to classify