On local orthonormal bases for classification and regression

@inproceedings{Saito1995OnLO,
  title={On local orthonormal bases for classification and regression},
  author={Naoki Saito and Ronald R. Coifman},
  booktitle={ICASSP},
  year={1995}
}
We describe extensions to the \best-basis" method to select orthonormal bases suitable for signal classiica-tion and regression problems from a large collection of orthonormal bases. For classiication problems, we select the basis which maximizes relative entropy of time-frequency energy distributions among classes. For regression problems, we select the basis which tries to minimize the regression error. Once these bases are selected, the most signiicant coordinates are fed into a traditional… CONTINUE READING
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