What is a clustering algorithm?
Clustering algorithm is a typical unsupervised learning algorithm, which is mainly used to automatically classify similar samples into one category.
In the clustering algorithm, samples are divided into different categories according to the similarity between samples. For different similarity calculation methods, different clustering results will be obtained. The commonly used similarity calculation method is the Euclidean distance method.
The clustering algorithm is unsupervised learning, which only needs data, not labeling results, and is used to find common groups through learning and training.
Understanding Clustering Algorithms
Using different clustering criteria, the resulting clustering results are different.
Application of clustering algorithm in reality
User portrait, advertisement recommendation, Data Segmentation, search engine traffic recommendation, malicious traffic identification
Business push based on location information, news clustering, screening and sorting
Image segmentation, dimensionality reduction, recognition; outlier detection; abnormal consumption of credit cards; discovery of gene fragments with the same function
The biggest difference between clustering algorithm and classification algorithm
Clustering algorithms are unsupervised learning algorithms, while classification algorithms are supervised learning algorithms.