Support vector machines (SVMs) is a statistical learning method with good performance when the sample size is small, due to their excellent performance, SVMs are now used extensively in pattern classification applications and regression estimation, Unfortunately, it is currently considerably slower in test phase caused by number of the support vectors, which has been a serious limitation for some application such as remotely sensed data classification. To overcome this problem, we introduced mean shift (MS) algorithm to select the feature vectors. Through the MS algorithm, the modes of data ar...
