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Multi-class classification can classify data into all the classes of interest, while single-class classification tells whether a given set of signals belong to the single class of interest. Multi-class projects need data and labels for all the classes of interest. Single-class projects need data only from a single class of interest, e.g., data from normal operating condition of a machine in an anomaly detection use case.