1. A pattern detection method comprising: approximating a decision surface in terms of multiple reduced set vectors; determining the presence of a particular pattern in an input pattern by sequentially evaluating and summing the kernelized inner product of the reduced set vectors with the input pattern, such that if at any point the input pattern can be rejected as not comprising the particular pattern, no more reduced set vectors are used for that input pattern and the pattern is rejected as a not comprising the particular pattern; and if all of the reduced set vectors are used on the input pattern, and the input pattern is not rejected, using a full support vector machine to classify the input pattern.