Издательство: | Книга по требованию |
Дата выхода: | июль 2011 |
ISBN: | 978-6-1303-5480-0 |
Объём: | 112 страниц |
Масса: | 190 г |
Размеры(В x Ш x Т), см: | 23 x 16 x 1 |
High Quality Content by WIKIPEDIA articles! Tikhonov regularization is the most commonly used method of regularization of ill-posed problems named for Andrey Tychonoff. In statistics, the method is also known as ridge regression. It is related to the Levenberg-Marquardt algorithm for non-linear least-squares problems. In several fields of mathematics, in particular statistics, machine learning and inverse problems, regularization involves introducing additional information in order to solve an ill-posed problem or prevent overfitting. This information is usually of the form of a penalty for complexity, such as restrictions for smoothness or bounds on the vector space norm.
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