A counter-example in linear feature selection theory

The paper shows that it is possible to construct two k x n matrices, both of which maximize divergence in the transformed space of the linear feature selection problem in multiclass pattern recognition, and which are not row equivalent. Thus, even under extremely strong conditions, it is not possible to assume that all matrix solutions which maximize transformed divergence are row equivalent.