  Any traditional classification problem in general involves modelling
individual classes and in turn classification by evaluating the similarity of
the test set with the modelled classes. In this paper, we introduce another
approach that would find the differential information between two classes
rather than modelling individual classes separately. The classes are viewed on
a common frame of reference in which one class would have a constant variance,
unlike the other class which would have unequal variance along its basis
vectors which would capture the differential information of one class over the
other.This, when mathematically formulated, leads to the solution of Matrix
Pencil equation.The theory of binary classification was extended to a
multi-class scenario.This is borne out by illustrative examples on the
classification of the MNIST database.
