Interpretation and Comparison of Multidimensional Data Partitions
نویسنده
چکیده
In this paper, a novel visualization method for partitions of multidimensional data is presented. It can be used for characterization of one or comparison of two partitions. The method nds the variables that best describe a partition or di erence between partitions. It is especially useful when the data set size is large and there are many variables, i.e., the data dimension is high. The method has been implemented in a software tool prototype which is used in analysis of operational states of a paper machine. For simplicity, however, use of the method is here demonstrated using the well-known Iris data set.
منابع مشابه
Interpretation and comparison of multivariate data partitions
In this paper, a novel visualization method for partitions of multidimensional data is presented. It can be used for characterization of one or comparison of two partitions. The method nds the variables that best describe a partition or di erence between partitions. It is especially useful when the data set size is large and there are many variables, i.e., the data dimension is high. The method...
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