Bibtex entry: Quantifying the computational complexity of the nearest features classifiers
@INPROCEEDINGS{Orozco2006c,
        author = {Orozco-Alzate, Mauricio and Castellanos-Dom{\'{\i}}nguez, C{\'{e}}sar Germ{\'{a}}n},
         month = {October},
         title = {Quantifying the computational complexity of the nearest features classifiers},
     booktitle = {Segundo Simposio Regional de Electr{\'{o}}nica y Aplicaciones Industriales IEEE},
          year = {2006},
         pages = {1--5},
  organization = {Universidad Aut{\'{o}}noma de Manizales},
       address = {Manizales, Colombia},
      abstract = {Nearest feature classifiers are extensions of the nearest-neighbor rule. This paper presents a quantification of the computational complexity of the nearest feature classifiers, by using an economic model which takes into account a trade-off between classifier error and evaluation complexity. The model was applied to the face recognition problem, which is the framework where these classifiers were originally proposed. Classifiers were also studied by measuring them in orders, denoted by the Landau symbol O.},
mytype={myconfs}
}
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