salmon: A Symbolic Linear Regression Package for Python
Fuente:
arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2019
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| Subjects: | |
| Online Access: | |
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| _version_ | 1866929294558625792 |
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| author | Boyd, Alex Sun, Dennis L. |
| author_facet | Boyd, Alex Sun, Dennis L. |
| contents | One of the most attractive features of R is its linear modeling capabilities. We describe a Python package, salmon, that brings the best of R's linear modeling functionality to Python in a Pythonic way -- by providing composable objects for specifying and fitting linear models. This object-oriented design also enables other features that enhance ease-of-use, such as automatic visualizations and intelligent model building. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_1911_00648 |
| institution | arXiv |
| publishDate | 2019 |
| record_format | arxiv |
| spellingShingle | salmon: A Symbolic Linear Regression Package for Python Boyd, Alex Sun, Dennis L. Computation One of the most attractive features of R is its linear modeling capabilities. We describe a Python package, salmon, that brings the best of R's linear modeling functionality to Python in a Pythonic way -- by providing composable objects for specifying and fitting linear models. This object-oriented design also enables other features that enhance ease-of-use, such as automatic visualizations and intelligent model building. |
| title | salmon: A Symbolic Linear Regression Package for Python |
| topic | Computation |
| url | https://arxiv.org/abs/1911.00648 |