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The main difference between classification and clustering are:
Clustering is an unsupervised learning method and classification is a supervised learning method. Process: – Clustering groups data points into clusters based on similarity.
Classification classifies the input data as one of the class labels of the output variable.
Both techniques have certain similarities, but the difference is that classification uses a defined class to which objects are assigned, whereas clustering identifies similarities between objects and follows these common characteristics. To group and distinguish from others.
In general, clustering consists of only one phase of his (grouping), whereas classification consists of two of his: training (where the model learns from the training set) and testing (where the target class is predicted). There are phases.
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