document: V-Miner : using enhanced parallel coordinates to mine product design and test data Analyzing data to find trends , correlations , and stable patterns is an important task in many industrial applications . This paper proposes a new technique based on parallel coordinate visualization . Previous work on parallel coordinate methods has shown that they are effective only when variables that are correlated and\/or show similar patterns are displayed adjacently . Although current parallel coordinate tools allow the user to manually rearrange the order of variables , this process is very time-consuming when the number of variables is large . Automated assistance is required . This paper introduces an edit-distance based technique to rearrange variables so that interesting change patterns can be easily detected visually . The Visual Miner ( V-Miner ) software includes both automated methods for visualizing common patterns and a query tool that enables the user to describe specific target patterns to be mined or displayed by the system . In addition , the system can filter data according to rules sets imported from other data mining tools . This feature was found very helpful in practice , because it enables decision makers to visually identify interesting rules and data segments for further analysis or data mining . This paper begins with an introduction to the proposed techniques and the V-Miner system . Next , a case study illustrates how V-Miner has been used at Motorola to guide product design and test decisions .
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