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scientific-intelligent-modelling/sim-datasets

SIM-Datasets: A Unified Symbolic Regression Benchmark A standardized benchmark collection designed for the Scientific Intelligent Modelling (SIM) toolkit, providing comprehensive datasets for symbolic regression research and applications. Overview SIM-Datasets serves as a unified benchmark for symbolic regression tasks, offering standardized datasets with consistent formatting and evaluation protocols. This collection is specifically curated to support the… See the full description on the dataset page: https://huggingface.co/datasets/scientific-intelligent-modelling/sim-datasets.

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SIM-Datasets: A Unified Symbolic Regression Benchmark

A standardized benchmark collection designed for the Scientific Intelligent Modelling (SIM) toolkit, providing comprehensive datasets for symbolic regression research and applications.

Overview

SIM-Datasets serves as a unified benchmark for symbolic regression tasks, offering standardized datasets with consistent formatting and evaluation protocols. This collection is specifically curated to support the Scientific Intelligent Modelling ecosystem, enabling researchers and practitioners to develop, test, and compare symbolic regression algorithms effectively.

Installation

Method 1: Git Clone

Clone the repository from Hugging Face:

bash

git lfs install
git clone https://huggingface.co/datasets/scientific-intelligent-modelling/sim-datasets

Or from ModelScope (for users in China):

bash

git lfs install
git clone https://www.modelscope.cn/datasets/scientific-intelligent-modelling/sim-datasets.git

Method 2: Python Package

Install via pip for seamless integration:

bash

pip install sim-datasets

License

This project is licensed under the GPL-3.0 License. See the LICENSE file for details.

Contributing

We welcome contributions! Please feel free to submit issues or pull requests to help improve this benchmark collection.