Latest version: v0.1.2
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fastSparseGAMs is a Python package that offers an efficient framework for solving L0-regularized learning problems in sparse generalized additive models (GAMs). Leveraging the L0Learn package, this package introduces two novel algorithms, namely quadratic cuts and dynamic feature ordering, to deliver faster computational speed. Additionally, it comes with a new loss function (exponential loss) for classification.
No known vulnerabilities found