skscope: Fast Sparse-Constraint Optimization#

skscope aims to make sparsity-constrained optimization (SCO) accessible to everyone because SCO holds immense potential across various domains, including machine learning, statistics, and signal processing. By providing a user-friendly interface, skscope empowers individuals from diverse backgrounds to harness the power of SCO and unlock its broad range of applications (see examples exhibited below).

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Installation

The simplest way to install skscope is running pip install skscope. Alternatively, you can install skscope from source following this instruction in the installation guide.

Quick Start

The quick example demonstrates the basic usage of skscope, which is remarkably straightforward. All you need is programming an objective function.

Examples Gallery

Comprehensive and hands-on examples that covers various machine learnings problems including regression analysis, survival analysis, graphical model, trend filtering, finance data analysis, and more.

Software Features

Introduce the advanced features provided by skscope, including the implemented iterative algorithms, practical helpful variants, toolkits for data science, and tips for improving computational efficiency.

API Reference

The reference guide of skscope provides a detailed description of the API. It offers information about the available classes and functions, along with their respective parameters.

Contributor’s Guide

Spot a typo in the documentation? Want to add new functionalities? Meet a bug? The contributing guide is here to assist you in addressing these issues.