Corrected Subspace Information Criterion for Least Mean Squares Learning
Xuejun Zhou · 2011
The least mean squares (LMS) algorithm is widely applied in the machine learning community. Corrected subspace information criterion (CSIC) is one of the model selection methods, which is defined on an unbiased estimator of the generalization error-subspace information criterion(SIC). In this paper, we will apply CSIC to select of LMS learning models, it can obtain better results than SIC.