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This article introduces the knowledge about "Python's method of achieving hierarchical clustering". In the actual case operation process, many people will encounter such difficulties. Next, let Xiaobian lead you to learn how to deal with these situations! I hope you can read carefully and learn something!

hierarchical clustering algorithm

As the name implies, hierarchical clustering is a layer of clustering, you can divide the large categories (clusters) from top to bottom, called split method; you can also aggregate small categories from bottom to top, called aggregation method; but generally used more is from bottom to top aggregation method.

Split Law:

Split method refers to the initial classification of all samples into a cluster, and then gradually split according to some criteria until a certain condition or a set number of classifications are reached. Description of algorithm:

Input: sample set D, number of clusters or some condition (usually a threshold for sample distance, so that the number of clusters can not be set)

Output: Cluster Results

1. classifying all samples in the sample set into a cluster;

repeat：

2. Calculate the distance between two samples in the same cluster (counted as c), and find the two samples a and b with the farthest distance;

3. assigning samples a, b to different clusters c1 and c2;

4. Calculate the distance between the remaining sample points in the original cluster (c) and a, b, if dis(a)

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