Rank-based methods for shrinkage and selection with application to machine learning
Robust statistics is an important field in contemporary mathematics and applied statistical methods. Rank-Based Methods for Shrinkage and Selection: With Application to Machine Learning describes techniques to produce higher quality data analysis in shrinkage and subset selection to obtain parsimoni...
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| Other Authors: | , , |
| Format: | eBook |
| Language: | English |
| Published: |
Hoboken, NJ
Wiley
2022
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| Edition: | Edition 2022 |
| Subjects: | |
| Online Access: | |
| Collection: | Wiley Online Books - Collection details see MPG.ReNa |
| Summary: | Robust statistics is an important field in contemporary mathematics and applied statistical methods. Rank-Based Methods for Shrinkage and Selection: With Application to Machine Learning describes techniques to produce higher quality data analysis in shrinkage and subset selection to obtain parsimonious models with outlier-free prediction. This book is intended for statisticians, economists, biostatisticians, data scientists and graduate students. |
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| Physical Description: | xxxi, 448 Seiten |
| ISBN: | 9781119625438 9781119625421 9781119625414 |