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Generating synthetic data is useful when you have imbalanced training data for a particular class, for example, generating synthetic females in a dataset of employees that has many males but few ...

Dr. James McCaffrey of Microsoft Research tackles the process of examining a set of source data to find data items that are different in some way from the majority of the source items. Data anomaly ...

Detecting changes in asset co-movements is of great importance to financial practitioners, with numerous risk management benefits arising from the timely detection of breakdowns in historical ...