The itca Python package offers an information-theoretic criterion to assist practitioners in combining ambiguous outcome labels by balancing the tradeoff between prediction accuracy and classification resolution. This article provides instructions for installing the itca Python package, demonstrates how to evaluate the criterion, and showcases its application in real-world scenarios for guiding the combination of ambiguous outcome labels.

中文翻译：

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用于信息理论分类准确性的 Python 包 itca：指导多类分类中模糊结果标签的数据驱动组合的标准。

itca Python 包提供了信息论标准，可帮助从业者通过平衡预测准确性和分类分辨率之间的权衡来组合模糊的结果标签。本文提供了安装 itca Python 包的说明，演示了如何评估该标准，并展示了其在实际场景中的应用，以指导不明确的结果标签的组合。