Difference Between Classification and Clustering

AlgorithmsMachine LearningSoftware & Coding

In this post, we will understand the difference between classification and clustering.


  • It is used with supervised learning.

  • It is a process where the input instances are classified based on their respective class labels.

  • It has labels hence there is a need to train and test the dataset to verify the model.

  • It is more complex in comparison to clustering.

  • Examples: Logistic regression, Naive Bayes classifier, Support vector machines.


  • It is used with unsupervised learning.

  • It groups the instances based on how similar they are, without using class labels.

  • It is not needed to train and test the dataset.

  • It is less complex in comparison to classification.

  • Examples: k-means clustering algorithm, Gaussian (EM) clustering algorithm.

Updated on 25-Mar-2021 06:03:56