Noisy Data in Data Mining (2009)

2009 (8 papers)

  • Khoshgoftaar TM, Van Hulse J. Empirical case studies in attribute noise detection. IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews 2009;39(4):379-88.
  • Mannino M, Yang Y, Ryu Y. Classification algorithm sensitivity to training data with non representative attribute noise. Decis Support Syst 2009;46(3):743-51.
  • Conrey B, Gold JM. Pattern recognition in correlated and uncorrelated noise. Journal of the Optical Society of America A: Optics and Image Science, and Vision 2009;26(11):B94-B109.
  • Ma PCH, Chan KCC. An iterative data mining approach for mining overlapping coexpression patterns in noisy gene expression data. IEEE Transactions on Nanobioscience 2009;8(3):252-8.
  • Al Shalabi LA. Improving accuracy and coverage of data mining systems that are built from noisy datasets: A new model. Journal of Computer Science 2009;5(2):131-5.
  • Libralon GL, de Carvalho ACPLF, Lorena AC. Pre-processing for noise detection in gene expression classification data. Journal of the Brazilian Computer Society 2009;15(1):3-11.
  • Mannino M, Yang Y, Ryu Y. Classification algorithm sensitivity to training data with non representative attribute noise. Decis Support Syst 2009;46(3):743-51.
  • Igawa K, Ohashi H. A negative selection algorithm for classification and reduction of the noise effect. Applied Soft Computing Journal 2009;9(1):431-8.