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Ridge regression is the most general algorithm for regression. It generalises all the regression methods implemented in this library as the problem of finding W such that the error e = (|| y-Wx ||) is minimised. Although it computational cost could be a little bigger for the already existing methods, It cover all the dimensionalities and all the function families:
Ridge regression is the most general algorithm for regression. It generalises all the regression methods implemented in this library as the problem of finding W such that the error e = (|| y-Wx ||) is minimised. Although it computational cost could be a little bigger for the already existing methods, It cover all the dimensionalities and all the function families:
[https://en.wikipedia.org/wiki/Tikhonov_regularization]
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