Cascading classifiers
Encyclopedia
Cascading is based on the concatenation of several classifiers, using all information collected from the output from a given classifier as additional information for the next classifier in the cascade. Unlike voting or stacking ensembles, which are multiexpert systems, cascading is a multistage one.

Notations

  • J. Gama and P. Brazdil. Cascade Generalization. Machine Learning, 41(3):315--343, 2000. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.46.635
  • J. Minguillón. On Cascading Small Decision Trees. PhD dissertation. Universitat Autònoma de Barcelona, 2002. http://www.tesisenxarxa.net/TESIS_UAB/AVAILABLE/TDX-1209102-150635/jma1de1.pdf
  • H. Zhao and S. Ram. Constrained Cascade Generalization of Decision Trees. IEEE Transactions on Knowledge and Data Engineering, 16(6):727--739, 2004.
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