基于平行坐标图的特征提取方法研究

Cui Jianxin, H. Wen-xue, Gao Haibo
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引用次数: 0

摘要

提出了一种基于平行坐标图的特征提取方法。观察平行坐标图,发现用一个维度上点到其他点的距离来衡量变量的分类性能,可以更客观地表达分类性能的事实。给出了欧几里德距离或模矩阵和相对距离矩阵。每个样本点与其他类别的距离之比以及与自己类别的距离之比具有更多的分类信息。在统计性能较差的数据上进行实验,取得了较好的效果。
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Study on Feature Extraction Method Based on Parallel Coordinate Plots
A novel feature extraction method based on parallel coordinate plots was presented. Observing the parallel coordinate plots, discovered that using the distance of one point to others on one dimensionality to measurement the classify performance of the variable, can express the fact classify performance more impersonally. The Euclidean distance or module matrix and the relative distance matrix were given. And the distance ratio of every sample point to other sorts and it to its own sort has more classify information. We achieved better performance when experiment on data which has poor statistical performance.
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