| 摘要 |
Systems, methods, and media that: implement a boosted classifier having a plurality of weak hypotheses that produce a classification, each of the plurality of weak hypotheses having at least one weight; receive testing data; receive at least one piece of training data subsequently to receiving the testing data; calculate corrective terms for correcting a sum of weights of correctly classified training data and a sum of weights of incorrectly classified training data; calculate the sum of weights of correctly classified training data and the sum of weights of incorrectly classified training data based on the corrective terms; modify the at least one weight of at least one of the plurality of weak hypotheses in response to the at least one piece of training data based on the sum of weights to produce modified weights; and classify the testing data based on the modified weights to produce a classification. |
