High-Dimensional Binary Pattern Classification by Scalar Neural Network Tree

  • Vladimir Kryzhanovsky
  • Magomed Malsagov
  • Juan Antonio Clares Tomas
  • Irina Zhelavskaya
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8681)


The paper offers an algorithm (SNN-tree) that extends the binary tree search algorithm so that it can deal with distorted input vectors. Perceptrons are the tree nodes. The algorithm features an iterative solution search and stopping criterion. Unlike the SNN-tree algorithm, popular methods (LSH, k-d tree, BBF-tree, spill-tree) stop working as the dimensionality of the space grows (N > 1000). With such high dimensionality, our algorithm works 7 times faster than the exhaustive search algorithm.


Nearest neighbor searching perceptron search tree hierarchical classifier multi-class classification 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Friedman, J.H., Bentley, J.L., Finkel, R.A.: An algorithm for finding best matches in logarithmic expected time. ACM Transactions on Mathematical Software 3, 209–226 (1977)CrossRefzbMATHGoogle Scholar
  2. 2.
    Liu, T., Moore, A.W., Gray, A., Yang, K.: An Investigation of Practical Approximate Nearest Neighbor Algorithms. In: Proceeding of the Conference on Neural Information Processing Systems (2004)Google Scholar
  3. 3.
    Indyk, P., Motwani, R.: Approximate nearest neighbors: Towards removing the curse of dimensionality. In: Proc. 30th STOC, pp. 604–613 (1998)Google Scholar
  4. 4.
    Beis, J.S., Lowe, D.G.: Shape Indexing Using Approximate Nearest-Neighbour Search in High-Dimensional Spaces. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 1000–1006 (1997)Google Scholar
  5. 5.
    Kryzhanovsky, B., Kryzhanovsky, V., Litinskii, L.: Machine Learning in Vector Models of Neural Networks. In: Koronacki, J., Raś, Z.W., Wierzchoń, S.T., Kacprzyk, J. (eds.) Advances in Machine Learning II. SCI, vol. 263, pp. 427–443. Springer, Heidelberg (2010)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Vladimir Kryzhanovsky
    • 1
  • Magomed Malsagov
    • 1
  • Juan Antonio Clares Tomas
    • 2
  • Irina Zhelavskaya
    • 3
  1. 1.Scientific Research Institute for System AnalysisRussian Academy of SciencesRussia
  2. 2.Institute of Secondary Education: IES SANJEMurciaSpain
  3. 3.Skolkovo Institute of Science and TechnologyMoscowRussia

Personalised recommendations