| 摘要 |
One embodiment of the present invention provides a system that optimizes a regression model which predicts a signal as a function of a set of available signals. During operation, the system receives training data for the set of available signals from a computer system during normal fault-free operation. The system also receives an objective function which can be used to evaluate how well a regression model predicts the signal. Next, the system initializes a pool of candidate regression models which includes at least two candidate regression models, wherein each candidate regression model in the pool includes a subset of the set of available signals. The system then optimizes the regression model by iteratively: (1) selecting two regression models U and V from the pool of candidate regression models, wherein regression models U and V best predict the signal based on the training data and the objective function; (2) using a genetic technique to create an offspring regression model W from U and V by combining parts of the two regression models U and V; and (3) adding W to the pool of candidate regression models.
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