This article Difference Between Classification and Clustering in Machine learning will tell you 12 key differences between Classification and Clustering in a tabular form. Classification and clustering are two main techniques that are used in machine learning and AI for performing retrieval of information, investigation of images and other tasks. Mainly clustering and classification algorithms are used for detecting diseases, crime and poverty-related factors. In this blog, we will learn the difference Between Classification And Clustering In Machine learning.
Classification
In machine learning and statistics, classification is the problem of categorizing to which of a set sub-populations, on the basis of a training set of data comprising observations whose category membership is known.
Clustering
It is the task of partitioning the population into a number of sets such that data points in the same groups are more alike to other data points in the same group and unlike the data points in other groups.
| S.No. | Features | Classification | Clustering |
| 1. | Definition | It is the process of categorization, in which ideas are organised. | It is a technique of establishing a collection of data into classes and clusters where the objects with high resemblance reside inside a cluster and the constituents of two clusters would be unalike to each other. |
| 2. | Data used | Supervised data | Unsupervised data |
| 3. | Phases | It has two phases | It has a single-phase |
| 4. | Value | It has a high-value training set | Its training set value is less as compared to the classification |
| 5. | Type of data | Labeled data is deployed | Unlabeled data is deployed |
| 6. | Popular Algorithms | NAIVE BAYES, decision tree, etc. | Mean shift clustering and K-means clustering |
| 7. | Complexity | It is more complex | It is not as much complex like classification |
| 8. | Boundary conditions | It must be specified. | It is not a mandate to specify. |
| 9. | Output value | The output value is known | The output value is unknown |
| 10. | Class knowledge | Prior knowledge of class | No prior knowledge of class |
| 11. | Prediction | Deals with predictive data | Doesn’t deal with prediction |
| 12. | Diagram |
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In this blog, we have read the differences between classification and clustering. If you are having any doubts, feel free to as me in the comment section.
