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Anomaly detection is an important task in data mining. Traditionally most of the anomaly detection algorithms have been designed for ‘static’ datasets, in which all the observations are available
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and children's observed birth events and their actual health and well-being outcomes. The latest machine learning and artificial intelligence advancements can mine these datasets to create prediction
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Edwards and D L Dowe (1998). "Single factor analysis in MML mixture modelling ", pp96 -109 , 2nd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD98), Lecture Notes in Artificial
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