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Relative quantity and allocation disagreement measures for category-level accuracy assessment

机译:类别级别准确性评估的相对数量和分配不一致措施

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摘要

Accuracy assessment of classified imagery is an important task in remote sensing. A commonly used approach for assessing classification accuracy is based on the error matrix. The error matrix can be summarized by overall and category accuracy measures, e.g. the overall agreement and the user's and producer's accuracies. Two relatively new measures are the so-called quantity disagreement and allocation disagreement. In this article, relative versions of the category-level variants of these measures are defined. It is also shown how the new category measures are related to the overall quantity and allocation disagreement measures.
机译:分类图像的准确性评估是遥感的重要任务。评估分类准确性的常用方法是基于误差矩阵。误差矩阵可以通过整体和类别精度度量来总结,例如总体协议以及用户和生产者的准确性。两种相对较新的措施是所谓的数量分歧和分配分歧。在本文中,定义了这些度量的类别级别变体的相对版本。还显示了新类别度量与总数量和分配不一致度量之间的关系。

著录项

  • 来源
    《International journal of remote sensing》 |2015年第24期|5959-5969|共11页
  • 作者

    Warrens Matthijs J.;

  • 作者单位

    Leiden Univ, Inst Psychol Methodol & Stat, Leiden, Netherlands;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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