LVQ_PAK

LVQ PAK: the learning vector quantization program package. An overview of the software package LVQPAK, which has been developed for convenient and effective application of learning vector quantization algorithms, is presented. Two new features are included: fast conflict-free initial distribution of codebook vectors into the class zones and the optimized-learning-rate algorithm OLVQ1.


References in zbMATH (referenced in 30 articles )

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  1. Schleif, Frank-Michael; Zhu, Xibin; Hammer, Barbara: Sparse conformal prediction for dissimilarity data (2015)
  2. Kaden, M.; Lange, M.; Nebel, D.; Riedel, M.; Geweniger, T.; Villmann, T.: Aspects in classification learning -- review of recent developments in learning vector quantization (2014)
  3. Hino, Hideitsu; Murata, Noboru: Information estimators for weighted observations (2013)
  4. Bunte, Kerstin; Biehl, Michael; Hammer, Barbara: A general framework for dimensionality-reducing data visualization mapping (2012)
  5. Jin, Xiao-Bo; Liu, Cheng-Lin; Hou, Xinwen: Regularized margin-based conditional log-likelihood loss for prototype learning (2010)
  6. Tambouratzis, Tatiana: An artificial neural network based approach for online string matching/filtering of large databases (2010)
  7. Venna, Jarkko; Peltonen, Jaakko; Nybo, Kristian; Aidos, Helena; Kaski, Samuel: Information retrieval perspective to nonlinear dimensionality reduction for data visualization (2010)
  8. Camastra, Francesco: A SVM-based cursive character recognizer (2007)
  9. Kim, Sang-Woon; Oommen, B. John: Prototype reduction schemes applicable for non-stationary data sets (2006)
  10. Lozano, M.; Sotoca, J. M.; Sánchez, J. S.; Pla, F.; Pȩkalska, E.; Duin, R. P. W.: Experimental study on prototype optimisation algorithms for prototype-based classification in vector spaces (2006)
  11. Aiolli, Fabio; Sperduti, Alessandro: Multiclass classification with multi-prototype support vector machines (2005)
  12. Bermejo, Sergio; Cabestany, Joan: Local averaging of ensembles of LVQ-based nearest neighbor classifiers (2004)
  13. Peltonen, Jaakko; Klami, Arto; Kaski, Samuel: Improved learning of Riemannian metrics for exploratory analysis (2004)
  14. Bote-Lorenzo, Miguel L.; Dimitriadis, Yannis A.; Gómez-Sánchez, Eduardo: Automatic extraction of human-recognizable shape and execution prototypes of handwritten characters. (2003) ioport
  15. Prabhakar, Salil; Jain, Anil K.; Pankanti, Sharath: Learning fingerprint minutiae location and type. (2003) ioport
  16. Smaoui, Nejib; Matar, Matar Ibrahim: Classification of human faces using Karhunen-Loève decomposition and radial basis function neural networks (2003)
  17. Tambouratzis, G.; Tambouratzis, T.; Tambouratzis, D.: Clustering with artificial neural networks and traditional techniques (2003)
  18. Aiolli, Fabio; Sperduti, Alessandro: A re-weighting strategy for improving margins (2002)
  19. Bermejo, Sergio; Cabestany, Joan: Oriented principal component analysis for large margin classifiers. (2001) ioport
  20. Kim, Soo H.; Jeong, Seonhwa; Suen, Ching Y.: A lexicon-driven approach for optimal segment combination in off-line recognition of unconstrained handwritten Korean words (2001)

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