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State the difference between clustering and classification
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CLASSIFICATION CLUSTERING
Classification is supervised learning technique used to assign per-defined tag to instance on the basis of features Clustering is unsupervised technique used to group similar instances on the basis of features.
Classification algorithm requires training data. Clustering does not require training data.
Classification,model is uses pre-defined instances. Clustering does not assign pre-defined label to each and every group.
With classification the groups (or classes) are specified before hand, with each training data instance belonging to a particular class. With clustering the groups (or clusters) are based on the similarities of data instances to each other.
Classification algorithms are supposed to learn the association between the features of the instance and the class they belong to. No predefined output class is used in training and the clustering algorithm is supposed to learn the grouping.
Example : An insurance company trying to assign customers into high risk and low risk categories. Example : An online movie company recommending you a movie because other customers who had made similar movie choices as you in the past have favorably rated that movie.
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