ACR:平均分类率
在商业与人力资源管理领域,“平均分类率”是一个常用指标,其英文全称为Average Classification Rate,通常缩写为ACR,以便于书面和口头交流的简洁高效。该术语主要用于衡量岗位或产品在特定标准下的平均归类效率,是评估业务流程、组织效能的重要参考依据。
Average Classification Rate具体释义
Average Classification Rate的英文发音
例句
- The experimental results on the synthetic data as well as the real world patterns demonstrate that the proposed approach can efficiently maintain an accurate low dimensional representation of the manifold data with less distortion, and give higher average classification rate compared to others. 2.
- 基于人造数据和实际数据的实验结果都验证了该算法能够有效地得到流形数据的低维表示,且提高分类器的平均分类率(ACR)。
- The first method is based on the exclusion of attribute terms that can achieve a higher average classification accuracy rate and generate less fuzzy rules than the existing methods.
- 第一种方法的基础概念是排除不需要的属性项目,此方法的平均分类准确度比目前已存在的方法高,所产生的模糊规则数目也比目前已存在的方法少。
- The results show that, this model can classify still natural images effectively with an average classification correct rate of 84.4 %.
- 在SIMPLIcity图像数据库上进行语义分类实验结果表明,该模型能对静止的自然图像进行有效分类,平均分类正确率为84.4%。
- Experiments show that the average classification accuracy rate can be above 90 % for either LSB replacement or matching steganography.
- 实验表明,分别对LSB替换、匹配隐写进行分析,平均分类正确率可以达到90%以上。
- Subsequences length and average accuracy values are compared under classification method with default rule. Experiments show that this intrusion detection method can have low false positive and high detection rate.
- 分析了在含有默认规则的检测方法下,滑窗长度和平均检测率以及规则数目之间的变化,实验结果表明该方法具有较高的平均检测率和检测速度。
本站英语缩略词为个人收集整理,可供非商业用途的复制、使用及分享,但严禁任何形式的采集或批量盗用
若ACR词条信息存在错误、不当之处或涉及侵权,请及时联系我们处理:675289112@qq.com。