One liner for Classification:
Classifying data into pre-defined categories
One liner for Clustering:
Grouping data into a set of categories
Key difference:
Classification is taking data and putting it into pre-defined categories and in Clustering the set of categories, that you want to group the data into, is not known beforehand.
Conclusion:
- Classification assigns the category to 1 new item, based on already
labeled items while Clustering takes a bunch of unlabeled items and
divide them into the categories
- In Classification, the categories\groups to be divided are known
beforehand while in Clustering, the categories\groups to be divided
are unknown beforehand
- In Classification, there are 2 phases – Training phase and then the
test phase while in Clustering, there is only 1 phase – dividing of
training data in clusters
- Classification is Supervised Learning while Clustering is
Unsupervised Learning
I have written a long post on the same topic which you can find here:
https://neelbhatt40.wordpress.com/2017/11/21/classification-and-clustering-machine-learning-interview-questions-answers-part-i/
