nexciting to me at first: basically, if we have enough feature dimensions we can almost always find a linear separation. This is also related to how Support Vector Machines work: they project the data into an extremely high-dimensional space, find a separating hyperplane with linear regression, and then project that pl

allows easy integration with a cognition system » (like mine). >> For instance, the face recognizer we built for the Brazilian >> government uses Support Vector Machines (SVMs) for the machine >> learning component (together with some hand-tuned feature extractors). >> That works OK for face recognition under approp