Soft multi-modal data fusion

S. Coppock, L. Mazlack
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引用次数: 5

Abstract

Clustering groups items together that are most similar to each other and sets those that are least similar into different clusters. Methods have been developed to cluster records in a data set that are of only qualitative or quantitative data. Data sets exist that contain a mix of qualitative (nominal and ordinal) and quantitative (discrete and continuous) data. Clustering records of mixed kinds of data is a difficult problem. A metric to measure the similarity between records of mixed data types is needed. Once a clustering is found, we do not know how to best evaluate the quality of the clustering when there is a mixture of data varieties.
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软多模态数据融合
聚类将彼此最相似的项组合在一起,并将最不相似的项设置到不同的聚类中。已经开发出方法,在只有定性或定量数据的数据集中对记录进行聚类。存在的数据集包含定性(名义和有序)和定量(离散和连续)数据的混合。混合类型数据的记录聚类是一个难题。需要一个度量来度量混合数据类型记录之间的相似性。一旦发现了聚类,当存在混合数据品种时,我们不知道如何最好地评估聚类的质量。
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