TPOT: 自动化的sklearn

Posted 2021-05-21 Data+Science+Insight

TPOT主页

https://epistasislab.github.io/tpot/

注意TPOT和sklearn的天然亲缘关系。

主页提供了许多常用数据集的示例：

选择超参数的问题在于，没有放之四海而皆准的超参数。 因此，对于每个新数据集，我们必须找到最佳设置。 这可能是一个耗时的过程，但幸运的是，在Scikit-Learn中执行此过程有多种选择，例如网格搜索和随机搜索。

更好的是，新的libraries，如epistasis实验室的TPOT 旨在为你自动完成此过程！

Consider TPOT your Data Science Assistant. TPOT is a Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

TPOT will automate the most tedious part of machine learning by intelligently exploring thousands of possible pipelines to find the best one for your data.

An example machine learning pipeline

Once TPOT is finished searching (or you get tired of waiting), it provides you with the Python code for the best pipeline it found so you can tinker with the pipeline from there.

An example TPOT pipeline

TPOT is built on top of scikit-learn, so all of the code it generates should look familiar... if you're familiar with scikit-learn, anyway.

TPOT is still under active development and we encourage you to check back on this repository regularly for updates.