Two examples: general interpretation clustering and Classification

Entry Level

Clustering:

There are 30 students in a class, and each student has 10 different photos, which disrupt the 300 photos,Clustering means learning 300 photos without telling the machine any student information, and then dividing it into 10 categories.;

Category

There are 30 students in a class, and each student has 10 different photos. The name of the student is written on each photo,Classification means that the machine learns the names of these 300 photos and photos to form a model that contains 10 categories. This model is used to predict which category the unknown photos belong.

 

Advanced Class

Clustering:

Unsupervised learning. Clustering refers to the process of finding out the cause of clustering between things through a group analysis without "tags.

Category:

Supervised Learning is to tag Objects Based on certain standards and then classify objects based on tags.

 

Note: The entry level is my rough understanding of clustering and classification, helping people who are new to classification and clustering quickly understand the difference. Of course, my understanding is still superficial, and there may be some inaccuracy in the expression. Hope you can see me! Thank you.

Two examples: general interpretation clustering and Classification