Feature selection on wide multiclass problems using OVA-RFEdoi:10.4114/IA.V13I44.1043Pablo M. GranittoAndrés BurgosAsociación Española para la Inteligencia Artificial (AEPIA)
Further, in the test phase OVA Tree Multiclass, due to its Log complexity, it is much faster than other methods in problems that have big class number. In this context, two corpus are used to evaluate our framework; TIMIT datasets for vowels classification and MNIST for recognition of ...
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