.png){kind=icon}
返回
Instance selection based on boosting for instance-based learners
.png){kind=icon}
PRE
AI
DOI：10.1016/j.patcog.2019.07.004.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Instance selection is one of the most important preprocessing steps in many machine learning tasks. Due to huge data size that is common in many current problems, removing redundant, useless, erroneous or noisy instances is a frequent initial step that is performed before other data mining algorithms are applied. Instance selection as part of this data reduction task is a relevant problem in current data mining research. Many instance selection methods hypothesize a certain way of characterizing the most important instances and then implement an algorithm to keep those important instances. The problem with these methods is that their success depends on the data fulfilling the underlying hypothesis. Other methods just add or delete instances considering only their effect on the accuracy of the nearest neighbor rule. In this paper, we present a new method of this second kind that uses boosting to obtain a subset of instances that is able to improve the classification accuracy of the whole dataset with a significant reduction. The instances are incrementally added by selecting those that maximize the accuracy of the subset using the weighting of instances from the construction of ensembles of classifiers and the step-wise addition of new instances. The method is compared using a large set of 205 different datasets with standard methods and shows the best overall performance. (C) 2019 Elsevier Ltd. All rights reserved.
Keyword:
Instance selection
Boosting
Instance-based learning
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
7.6
论文数:
1.3W
被引数:
4.5W
机构
引用论文
.png){kind=icon}
An Evolutionary Multiobjective Model and Instance Selection for Support Vector Machines With Pareto-Based Ensembles基于Pareto集成的支持向量机的进化多目标模型和实例选择
PREAI
分享收藏Toward an efficient fuzziness based instance selection methodology for intrusion detection system
PREAI
分享收藏Transfer Boosting With Synthetic Instances for Class Imbalanced Object Recognition使用合成实例进行类不平衡对象识别的转移增强
PREAI
分享收藏
查看更多内容