Difference between classification and clustering in data mining?
Can someone explain the basic difference between classification and clustering? Provide some examples.
Following are the differences between classification and clustering-
1. Classification is the process of classifying the data with the help of class labels whereas, in clustering, there are no predefined class labels.
2. Classification is supervised learning, while clustering is unsupervised learning.
3. In Classification, algorithms like Decision trees, Bayesian classifiers are used whereas, in Clustering, algorithms like K-means, Expectation-Maximization is used.
4. Classification has prior knowledge of classes but the cluster doesn't have any prior knowledge of classes.
Example of classification: classification between gender.
Example of a cluster: discovery of patterns.
Hope, the difference between classification and clustering helps you in choosing the best for you.