Metric-based neural network classification tool for analyzing large-scale software

R. Paul
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引用次数: 9

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.<>
基于度量的神经网络分类工具,用于分析大型软件
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
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