首页> 美国卫生研究院文献>other >The effect of class imbalance on case selection for case-based classifiers: An empirical study in the context of medical decision support

【2h】

The effect of class imbalance on case selection for case-based classifiers: An empirical study in the context of medical decision support

机译：基于案例分类机的类别不平衡的效果：医学决策支持背景下的实证研究

代理获取

本网站仅为用户提供外文OA文献查询和代理获取服务，本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文，但由于OA文献来源多样且变更频繁，仍可能出现获取不到、文献不完整或与标题不符等情况，如果获取不到我们将提供退款服务。请知悉。

页面导航

摘要
著录项
相似文献
相关主题

摘要

Case selection is a useful approach for increasing the efficiency and performance of case-based classifiers. Multiple techniques have been designed to perform case selection. This paper empirically investigates how class imbalance in the available set of training cases can impact the performance of the resulting classifier as well as properties of the selected set. In this study, the experiments are performed using a dataset for the problem of detecting breast masses in screening mammograms. The classification problem was binary and we used a k-nearest neighbor classifier. The classifier’s performance was evaluated using the Receiver Operating Characteristic (ROC) area under the curve (AUC) measure. The experimental results indicate that although class imbalance reduces the performance of the derived classifier and the effectiveness of selection at improving overall classifier performance, case selection can still be beneficial, regardless of the level of class imbalance.

著录项

期刊名称 other
作者
Jordan M. Malof; Maciej A. Mazurowski; Georgia D. Tourassi;
展开▼
作者单位

展开▼
年(卷),期 -1(25),1
年度 -1
页码 002
总页数 11
原文格式 PDF
正文语种
中图分类
关键词
Case-based reasoning Computer-aided decision Class imbalance Case selection;

机译：基于案例的推理;计算机辅助决策;班级不平衡;案例选择;

相似文献

外文文献
中文文献
专利

1. The effect of class imbalance on case selection for case-based classifiers: an empirical study in the context of medical decision support. [J] . Malof JM, Mazurowski MA, Tourassi GD Neural Networks: The Official Journal of the International Neural Network Society . 2012,第Jana期

机译：类不平衡对基于病例的分类器的病例选择的影响：在医疗决策支持背景下的实证研究。
2. Comparative analysis of instance selection algorithms for instance-based classifiers in the context of medical decision support. [J] . Mazurowski MA, Malof JM, Tourassi GD Physics in medicine and biology. . 2011,第2期

机译：医疗决策支持环境下基于实例的分类器的实例选择算法的比较分析。
3. Feature Selection and Ensemble Learning Techniques in One-Class Classifiers: An Empirical Study of Two-Class Imbalanced Datasets [J] . Chih-Fong Tsai, Wei-Chao Lin Quality Control, Transactions . 2021,第1期

机译：单级分类器中的特征选择和集合学习技术：两级不平衡数据集的实证研究
4. The effect of class imbalance on case selection for case-based classifiers, with emphasis on computer-aided diagnosis systems [C] . Malof J.M., Mazurowski M.A., Tourassi G.D. International Joint Conference on Neural Networks;IJCNN 2009 . 2009

机译：类不平衡对基于案例的分类器的案例选择的影响，重点是计算机辅助诊断系统
5. Classifier design to improve pattern classification and knowledge discovery for imbalanced datasets. [D] . Wang, Kun. 2009

机译：分类器设计可改进模式分类和不平衡数据集的知识发现。
6. Training Neural Network Classifiers for Medical Decision Making: The Effects of Imbalanced Datasets on Classification Performance [O] . Maciej A. Mazurowski, Piotr A. Habas, Jacek M. Zurada, -1

机译：训练用于医疗决策的神经网络分类器：不平衡数据集对分类性能的影响
7. The effect of class imbalance on case selection for case-based classifiers: An empirical study in the context of medical decision support [O] . Jordan M. Malof, Maciej A. Mazurowski, Georgia D. Tourassi 2012

机译：基于案例分类机的类别不平衡的效果：医学决策支持背景下的实证研究

The effect of class imbalance on case selection for case-based classifiers: An empirical study in the context of medical decision support

摘要

著录项

相似文献

相关主题

期刊订阅