Image classification based on transductive support vector machines
基于直推式支持向量机的图像分类算法

Transductive Support Vector Machines (TSVM) take advantage of the test sets as well as the train sets and inherit most properties of inductive SVMs. They are more efficient than inductive SVMs, especially for very small training sets and large test sets. But they still have disadvantages, such as high time complexity and the requirement of "num ". The improved algorithm substantially reduces the time complexity with little influence on the performance.