Rectified nearest feature line segment for pattern classification
Rectified nearest feature line segment for pattern classification
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DOI：
10.1016/j.patcog.2006.10.021
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发表时间：
2007-05
期刊：
影响因子：
--
通讯作者：
Hao Du;Y. Chen
中科院分区：
文献类型：
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作者：
Hao Du;Y. Chen
指出并分析了最近特征线分类器的优点和不足。为了克服这一缺点，我们构造了一个新的特征子空间来表示每一个类别，并做了两个简单有效的改进。所提出的方法，被称为整流最近的特征线段（RNFLS），被证明具有一种新的属性的浓度作为一个结果的线段（功能），这显着提高了分类能力。另一个显著的优点是RNFLS适用于复杂的任务，如双螺旋分布，这是原来的NFL不能正确处理。最后，与NFL，NN（最近邻），k-NN和NNL（最近邻线）使用人工和真实世界的数据集的实验比较表明，RNFLS提供了最佳的性能。
This paper points out and analyzes the advantages and drawbacks of the nearest feature line (NFL) classifier. To overcome the shortcomings, a new feature subspace with two simple and effective improvements is built to represent each class. The proposed method, termed rectified nearest feature line segment (RNFLS), is shown to possess a novel property of concentration as a result of the added line segments (features), which significantly enhances the classification ability. Another remarkable merit is that RNFLS is applicable to complex tasks such as the two-spiral distribution, which the original NFL cannot deal with properly. Finally, experimental comparisons with NFL, NN(nearest neighbor), k-NN and NNL (nearest neighbor line) using both artificial and real-world data-sets demonstrate that RNFLS offers the best performance.