The most basic difference between clustering and classification.

The most basic difference between clustering and classification .

Classification simply put , According to the characteristics or attributes of the text , To divide into existing categories .

in other words , These categories are known , By training and learning the data of known classification , Find the characteristics of these different classes , Then classify the unclassified data .

The understanding of clustering is simpler , That is, you don't know how the data will be divided into , The data or users are aggregated into several groups through cluster analysis , That is clustering .

Clustering does not require data training and learning .

Classification belongs to supervised learning , Clustering belongs to unsupervised learning .

Common classification such as decision tree classification algorithm 、 Bayes classification algorithm, etc .

The most basic clustering algorithm is systematic clustering ,K-means Mean clustering , These are common , A big push for online materials , I won't repeat .

author ： Hua Tianqing
link ：https://www.zhihu.com/question/42044303/answer/102223996
source ： You know
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