Common Subset Selection of Inputs in Multiresponse Regression

  title={Common Subset Selection of Inputs in Multiresponse Regression},
  author={Timo Simil{\"a} and Jarkko Tikka},
  journal={The 2006 IEEE International Joint Conference on Neural Network Proceedings},
We propose the multiresponse sparse regression algorithm, an input selection method for the purpose of estimating several response variables. It is a forward selection procedure for linearly parameterized models, which updates with carefully chosen step lengths. The step length rule extends the correlation criterion of the least angle regression algorithm for many responses. We present a general concept and explicit formulas for three different variants of the algorithm. Based on experiments… CONTINUE READING
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