A dimension range representation (DRR) measure for self-organizing maps
作者：
Highlights：
• The self-organizing map is a popular technique for clustering and visualization.
• If the map vectors represent all dimensions of the data well, insight into the data set will be improved.
• A ‘dimension range representation’ measure is introduced to quantify coverage of the data by the map.
• Information gained from the map can be improved with optimal map size and shape.
• The DRR measure can be used to choose output map size and shape to improve insights.
摘要
•The self-organizing map is a popular technique for clustering and visualization.•If the map vectors represent all dimensions of the data well, insight into the data set will be improved.•A ‘dimension range representation’ measure is introduced to quantify coverage of the data by the map.•Information gained from the map can be improved with optimal map size and shape.•The DRR measure can be used to choose output map size and shape to improve insights.
论文关键词：Self-organizing maps,Quality,Error measure,Dimension,Coverage,Map size,Map shape,Extreme values
论文评审过程：Received 12 August 2014, Revised 13 September 2015, Accepted 7 November 2015, Available online 19 November 2015, Version of Record 8 February 2016.
论文官网地址：https://doi.org/10.1016/j.patcog.2015.11.002
