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在 AI 推理（尤其是大语言模型）的性能评估中，TTFT、TPOT 和 ITL 是关键指标，分别衡量首次响应时间、单个 Token 的生成效率以及系统整体延迟。 TPOT，作为一款自动化机器学习工具，其设计宗旨在于通过遗传编程自动优化机器学习的流程，使数据科学家和分析师能够更高效地完成模型的构建和参数的调优工作。 Tpot's intro as of tpot 19

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This season was created following the split of battle for bfdi, one being the 2nd half of the original season TPOT是一款强大的Python自动机器学习工具,它利用遗传编程来优化机器学习流水线,帮助数据科学家自动化繁琐的模型选择和超参数调优过程。 Battle for bfb and the other being battle for dream island

TPOT 是 Tree-based Pipeline Optimization Tool（基于树的流水线优化工具）的缩写。 TPOT 是一款 Python 自动化机器学习工具，它使用遗传编程来优化机器学习流水线。

Tpot is a python automated machine learning tool that optimizes machine learning pipelines using genetic programming. Tpot uses a version of genetic programming to automatically design and optimize a series of data transformations and machine learning models that attempt to maximize the classification accuracy for a given supervised learning data set. TPOT (Tree-based Pipeline Optimization Tool) 是一個自動化機器學習 (AutoML)的 Python 工具，主要是希望簡化機器學習模型的建模過程，TPOT利用遺傳編程來自動設計和優化機器學習管道，讓非專業的資料科學研究人員也能輕鬆使用機器學習技術。 TPOT是一个基于树的管道优化工具，用于Python的自动机器学习。 它利用遗传编程找到最佳的模型管道，支持分类和回归任务。