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Feature selection for multiclass discrimination via mixed-integer linear programming

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2 Author(s)
Iannarilli, F.J., Jr. ; Aerodyne Res. Inc., Billerica, MA, USA ; Rubin, P.A.

We reformulate branch-and-bound feature selection employing L or particular Lp metrics, as mixed-integer linear programming (MILP) problems, affording convenience of widely available MILP solvers. These formulations offer direct influence over individual pairwise interclass margins, which is useful for feature selection in multiclass settings.

Published in:

Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:25 ,  Issue: 6 )

Date of Publication:

June 2003

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