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Classification algorithms predict one or more discrete variables, based on the other attributes in the dataset.

Regression algorithms predict one or more continuous numeric variables, such as profit or loss, based on other attributes in the dataset.

Segmentation algorithms divide data into groups, or clusters, of items that have similar properties.

Association algorithms find correlations between different attributes in a dataset. The most common application of this kind of algorithm is for creating association rules, which can be used in a market basket analysis.

Sequence analysis algorithms summarize frequent sequences or episodes in data, such as a series of clicks in a web site, or a series of log events preceding machine maintenance.