ReHLine-python and ReHLine
The Python version is a language-specific wrapper/port of the original implementation, making them ecosystem siblings where the Python package provides accessibility to the core algorithm for Python users.
About ReHLine-python
softmin/ReHLine-python
Regularized Composite ReLU-ReHU Loss Minimization with Linear Computation and Linear Convergence
This tool helps data scientists and machine learning engineers quickly build and optimize machine learning models for classification, regression, and constrained optimization problems. You input your dataset and choose a model type (like Support Vector Machines or Huber Regression), and it efficiently computes the optimal model parameters. It's designed for practitioners who need to train high-performing models on large datasets.
About ReHLine
softmin/ReHLine
Regularized Composite ReLU-ReHU Loss Minimization with Linear Computation and Linear Convergence
ReHLine helps machine learning practitioners build models like SVMs, quantile regression, or Huber regression with speed and precision, even with large datasets or fairness requirements. It takes your raw data and desired model type, then quickly produces an optimized model ready for predictions. This tool is for data scientists, ML engineers, and researchers who need to train robust, high-performing predictive models for classification, regression, and risk assessment.
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