Introduction to the K-Means Clustering Algorithm Based on the Elbow Method

The K-means clustering algorithm is a commonly used algorithm in the financial field, and it is also an unsupervised learning algorithm. It is characterized as an easy and simple algorithm and is widely used in the fields such as machine learning and stock trading. However, the K-means algorithm also has certain shortcomings. The k value is difficult to determine, and the initial center of the cluster is difficult to find. This article introduces the idea of K-means algorithm, using the elbow method to find the most suitable k value.