새로운 적합도 함수를 사용한 비계량형 다차원 척도법에 대한 연구
A Study on Non-Metric Multidimensional Scaling Using A New Fitness Function
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Since the non-metric Multidimensional scaling (nMDS), a data visualization technique, provides with insights about engineering,economic, and scientific applications, it is widely used for analyzing large non-metric multidimensional data sets. The nMDS requires a fitness function to measure fit of the proximity data by the distances among n objects. Most commonly used fitness functions are nonlinear and have a difficulty to find a good configuration. In this paper, we propose a new fitness function, an absolute value type, and show its advantages.
Abstract
Since the non-metric Multidimensional scaling (nMDS), a data visualization technique, provides with insights about engineering,economic, and scientific applications, it is widely used for analyzing large non-metric multidimensional data sets. The nMDS requires a fitness function to measure fit of the proximity data by the distances among n objects. Most commonly used fitness functions are nonlinear and have a difficulty to find a good configuration. In this paper, we propose a new fitness function, an absolute value type, and show its advantages.
참고문헌 (18)
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