کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
383296 | 660815 | 2012 | 9 صفحه PDF | دانلود رایگان |
Visual data mining with virtual reality spaces is used for the representation of data and symbolic knowledge. High quality structure-preserving and maximally discriminative visual representations can be obtained using a combination of neural networks (SAMANN and NDA) and rough sets techniques, so that a proper subsequent analysis can be made. The approach is illustrated with two types of data: for gene expression cancer data, an improvement in classification performance with respect to the original spaces was obtained; for geophysical prospecting data for cave detection, a cavity was successfully predicted.
► Virtual reality is used for the representation of data and symbolic knowledge.
► High quality structure-preserving representations are obtained.
► A combination of neural networks and rough sets techniques is used.
► For gene expression cancer data, classification performance improves.
► For geophysical prospecting data, a cavity was successfully predicted.
Journal: Expert Systems with Applications - Volume 39, Issue 18, 15 December 2012, Pages 13193–13201