1. A computer-implemented method for determining a boundary for binary classification comprising: providing a data set of vectors corrupted by noise; initializing a value for uncertainty for each vector in the data set corrupted by noise; determining a hyperplane dividing the data set and a slack variable for each vector in the data set given a current value for uncertainty, wherein a weight of each vector on the hyperplane is varied according to the current value for uncertainty for the respective vector and wherein the weight of a respective vector is reduced with increased uncertainty; updating the value for uncertainty and the slack variable for each vector in the data set given the hyperplane; and determining the hyperplane to be the boundary for binary classification of the data set upon determining a termination criterion to be met, wherein the vectors of the data set are classified according to the boundary.