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Solving Multiclass Learning Problems via Error-Correcting Output Codes
[article]
1995
arXiv
pre-print
Multiclass learning problems involve finding a definition for an unknown function f(x) whose range is a discrete set containing k > 2 values (i.e., k "classes"). The definition is acquired by studying collections of training examples of the form [x_i, f (x_i)]. Existing approaches to multiclass learning problems include direct application of multiclass algorithms such as the decision-tree algorithms C4.5 and CART, application of binary concept learning algorithms to learn individual binary
arXiv:cs/9501101v1
fatcat:fvi6ddbhlnd4rhmmw6yewcteji