基于度量的神经网络分类工具,用于分析大型软件

R. Paul
{"title":"基于度量的神经网络分类工具,用于分析大型软件","authors":"R. Paul","doi":"10.1109/TAI.1992.246366","DOIUrl":null,"url":null,"abstract":"The neural network described performs classification of software metrics. It is a three-layer, error back-propagation network. Using historical data, the neural network learns the relationship between certain metrics and a particular classification. The neural network selects the classification which best fits the input metrics. The capability of neural networks to classify nonlinearly separable problem spaces gives them an advantage over tree-based and linear network-based classification methods. When applied to actual software metrics, the neural network correctly classified 100% of the data presented.<<ETX>>","PeriodicalId":265283,"journal":{"name":"Proceedings Fourth International Conference on Tools with Artificial Intelligence TAI '92","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Metric-based neural network classification tool for analyzing large-scale software\",\"authors\":\"R. Paul\",\"doi\":\"10.1109/TAI.1992.246366\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The neural network described performs classification of software metrics. It is a three-layer, error back-propagation network. Using historical data, the neural network learns the relationship between certain metrics and a particular classification. The neural network selects the classification which best fits the input metrics. The capability of neural networks to classify nonlinearly separable problem spaces gives them an advantage over tree-based and linear network-based classification methods. When applied to actual software metrics, the neural network correctly classified 100% of the data presented.<<ETX>>\",\"PeriodicalId\":265283,\"journal\":{\"name\":\"Proceedings Fourth International Conference on Tools with Artificial Intelligence TAI '92\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-11-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings Fourth International Conference on Tools with Artificial Intelligence TAI '92\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TAI.1992.246366\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Fourth International Conference on Tools with Artificial Intelligence TAI '92","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TAI.1992.246366","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

摘要

所描述的神经网络对软件指标进行分类。它是一个三层误差反向传播网络。利用历史数据,神经网络学习特定指标和特定分类之间的关系。神经网络选择最适合输入指标的分类。神经网络对非线性可分离问题空间进行分类的能力使其优于基于树和基于线性网络的分类方法。当应用于实际的软件度量时,神经网络正确分类了100%呈现的数据
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Metric-based neural network classification tool for analyzing large-scale software
The neural network described performs classification of software metrics. It is a three-layer, error back-propagation network. Using historical data, the neural network learns the relationship between certain metrics and a particular classification. The neural network selects the classification which best fits the input metrics. The capability of neural networks to classify nonlinearly separable problem spaces gives them an advantage over tree-based and linear network-based classification methods. When applied to actual software metrics, the neural network correctly classified 100% of the data presented.<>
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Applying a time map manager in a real-time expert system for alarm filtering Fault diagnosis of power distribution lines by using discrimination tree Algorithmic mapping of neural networks with multi-activation product units onto SIMD machines Learning object models in visual semantic networks A neuro-expert system architecture with application to alarm processing in a power system control centre
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1