Evaluation of supervised and unsupervised 3D star visualisation algorithms

Int J Data Min Bioinform. 2013;8(4):443-61. doi: 10.1504/ijdmb.2013.056612.

Abstract

The 3D Star Coordinate Projection (3DSCP) visualisation algorithm has been developed to address the following key issues: choosing the projection configuration autonomously. preserving the data topology after projection. enhancing resolution. A supervised version of 3DSCP (S3DSCP) is also introduced to improve the computational efficiency of 3DSCP. Comparison with other linear, non-linear and axis-based techniques is performed to illustrate the efficacy of the 3DSCP and S3DSCP methods. Empirical analyses indicate that the 3DSCP and S3DSCP algorithms find hidden patterns in data while overcoming limitations of other techniques.

Publication types

  • Comparative Study
  • Evaluation Study
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Algorithms*
  • Computational Biology / methods*
  • Image Processing, Computer-Assisted / methods*