Distance Learning Algorithm Comparing in Classification and Retrieval
نویسندگان
چکیده
Learning a good distance function is crucial in a lot of applications. Different Learning distance with different will effect the performance of application in different ways. The most closely related application is classification and retrieval task. In this report, three different distance learning algorithm, LMNN, Isomap and SimpleNPKL, is compared via their performance in three different kinds of application with various dataset to explore the characteristic of these algorithms and to compare them in a whole view. In the experiment a case of special over fitting was observed. It also report a new approach to improve the performance of Isomap via introduce side information to the algorithm.
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