Support Vector Data Description(SVDD)is introduced into multiple instance learning.Three multi-instance learning methods based on SVDD are presented

which include Multiple Instance Learning based on SVDD and bag classification(mi-SVDD)or instance classification(MI-SVDD)

and Multiple Instance Learning based on SVDD and positive instance prediction(SVDD-MILD-I).Experimental results on MUSK dataset show that precisions of mi-SVDD and MI-SVDD are quite comparable to those of mi-SVM and MI-SVM;SVDD-MILD-I can get highest accuracy among all the methods known so far.Experimental results in the application of content based image retrieval in COREL image collections demonstrate that precision achieved by SVDD-MILD_I is higher than the others.Additionally

SVDD-MILD_I discriminates the misclassification-prone images between Beach and Mountains quite well.