Abstract
This paper attempts to combine Laplacian Twin Support Vector Machine (Lap-TWSVM) and Decision Tree Twin Support Vector Machine classifier to obtain an effective tree based classifier for semi-supervised multi-category classification. This classifier is termed as Tree Based Multi-Category Laplacian Twin Support Vector Machine (TB-Lap-TWSVM) classifier. TB-Lap-TWSVM is an improved One Against All (OAA) partition based tree classifier which takes advantage of both Lap-TWSVM and Decision Tree methodology. This paper concentrates on the application of TB-Lap-TWSVM to Content Based Image Retrieval problem. Further, extensive experiments on color images are carried out on different databases to establish the efficacy of the proposed model vis a vis TB-Lap-SVM and OAA-Lap-TWSVM.
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