VISUALIZATION CLASSIFICATION METHOD OF MULTI-DIMENSIONAL DATA BASED ON RADAR CHART MAPPING

机译：基于雷达图映射的多维数据可视化分类方法

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Fourier descriptor is an important method used in shape analysis and recognition. A novel method for designing the classifier of multi-dimensional data was proposed, which used radar chart of multi-statistics to show multidimensional data and applied Fourier Descriptors to recognize the radar chart. Different multi-dimensional data formed different radar chart and distinguished different category. Then a new Fourier descriptor based on polar radius is defined, which describes curve of radar chart shape. The method of Probabilistic Neural network combined with Fourier Descriptors is used to implement automatic classification. Experimental results show this method has the good classification precision, and may compare with the traditional classifier.

机译：傅立叶描述符是一种用于形状分析和识别的重要方法。提出了一种设计多维数据分类器的新方法，该方法利用多统计雷达图显示多维数据，并应用傅立叶描述符对雷达图进行识别。不同的多维数据形成不同的雷达图并区分不同的类别。然后定义了一个新的基于极半径的傅立叶描述子，该描述子描述了雷达图形状的曲线。采用概率神经网络与傅立叶描述子相结合的方法来实现自动分类。实验结果表明，该方法具有良好的分类精度，可与传统分类器进行比较。

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《2008 International Conference on Machine Learning and Cybernetics（2008机器学习与控制论国际会议）论文集》|2008年|857-862|共6页
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WEN-YUAN LIU; BAO-WEN WANG; JIA-XIN YU; FANG LI; SHUI-XING WANG; WEN-XUE HONG;
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Data visualization; Radar chart; Fourier descriptors; Shape recognition; Probabilistic Neural network;

机译：数据可视化;雷达图;傅里叶描述符;形状识别;概率神经网络;

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VISUALIZATION CLASSIFICATION METHOD OF MULTI-DIMENSIONAL DATA BASED ON RADAR CHART MAPPING

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