statistical-python/yaglm
A python package for penalized generalized linear models that supports fitting and model selection for structured, adaptive and non-convex penalties.
This tool helps statisticians and data scientists build predictive models to understand complex data, like customer behavior or disease progression. You input structured data (like spreadsheets or databases) and get back a statistical model that highlights important factors and makes predictions, helping you make informed decisions. It's designed for quantitative analysts and researchers who need precise, interpretable models.
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Use this if you need to build robust, interpretable predictive models from your data and want fine-grained control over how the model identifies important features, including support for advanced sparsity and adaptive techniques.
Not ideal if you're looking for a simple, out-of-the-box solution for basic linear regression or classification without the need for advanced statistical customization or model interpretability.
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58
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16
Language
Python
License
MIT
Category
Last pushed
Feb 02, 2023
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