An increasing learning algorithm based on SVM
ZENG Rong, LIU Jian-cheng, JIANG Xin-hua(Information of Science and Technology, Central South University, Changsha 410075, China)
Compare to normal technology of data classifies, technology of data classify which have increasing learning ability have distinct advantage: it can take full advantage of history training result; it can reduce subsequence training time marked ness. This article introduces basic principle of SVM and normal increasing learning arithmetic. To some gradual change problem (such as forepart malfunction period and spoilage period of machine facility), new sample providers different information from history sample. This article puts forward a new kind of weight increasing learning algorithm, and gain better classify face through cycle. Simulate experiment shows that weight increasing learning algorithm can reflect character of new sample better.