METHOD AND APPARATUS FOR DETERMINING THE ACCURACY LIMIT OF A LEARNING MACHINE FOR PREDICTING PATH PERFORMANCE DEGRADATION IN A COMMUNICATIONS NETWORK

A method and apparatus for determining the accuracy limit of a learning machine for predicting path performance degradation imposed by the quality of the path performance data is disclosed. A plurality of learning machines of increasing capacity are trained using training data and tested using test data, and the training error rates and test error rates are calculated. The asymptotic error rates of the learning machines are calculated and compared. When the change in asymptotic error rate falls below a certain rate, the asymptotic error rate estimates the accuracy limit for a learning machine for predicting path performance degradation. The accuracy limit is derived from insufficiencies in the path performance data and is applicable to any learning machine trained on and applied to the path performance data, regardless of the complexity of the learning machine or the size of the training data set.