精选理由
想用Ax调超参数？这篇手把手教你配搜索空间、跑自适应实验，比随机搜索省事。
本教程演示如何用Meta的Ax客户端API进行自适应实验，调优RandomForest模型，在合成分类数据集上平衡预测准确率与模型体积。搜索空间涵盖整数、浮点、对数尺度和类别参数。教程包含从定义参数到运行实验的完整工作流代码，可直接套用到自己的调参任务。
原文 · marktechpost
Adaptive Experimentation with Meta’s Ax: A Practical Coding Guide
In this tutorial, we explore adaptive experimentation using Meta’s Ax with the modern Client API. We work through a complete workflow where we tune a RandomForest model on a synthetic classification dataset while balancing predictive accuracy against model footprint. We begin by defining a mixed search space with integer, float, log-scaled, and categorical parameters, then […] The post Adaptive Experimentation with Meta’s Ax: A Practical Coding Guide appeared first on MarkTechPost .