MODEL RESELECTION FOR ACCOMMODATING UNSATISFACTORY TRAINING DATA

An anomaly analysis system generates models capable of more accurately identifying anomalies in data that contains unsatisfactory training data. The anomaly analysis system determines when data contains unsatisfactory training data. When an anomaly is detected in data using an initially selected model, and the data contains unsatisfactory training data, model reselection is performed. The reselected model analyzes the data. The reselected model is used to identify any anomalies in the data based on a data point from the data being outside of a confidence interval related to a predicted point by the reselected model corresponding to the data point.