Decision-Tree-Based Support Vector Machines

Decision Tree as an Accelerator for Support Vector Machines

Support vector machine (SVM) is known to be a very powerful learning machine for pattern classification, of which optical character recognition (OCR) naturally falls as a branch. There are, however, a few hindrances in making an immediate application of SVM for the OCR purpose. First, to construct a well-performing SVM character recognizer has to deal with a large set of training samples (hundr...

Using Decision Tree Based Multiclass Support Vector Machines for Forest Mapping

The goal of this study is to develop an automatic supervised classification strategy and to find the necessary data sources to perform automatic tree species classification on single tree level for a large area. The derived forest map is used in a virtual forest testbed to estimate additional forest parameters like diameter at breast height and volume at single tree and stand level. A virtual f...

STAGE-DISCHARGE MODELING USING SUPPORT VECTOR MACHINES

Establishment of rating curves are often required by the hydrologists for flow estimates in the streams, rivers etc. Measurement of discharge in a river is a time-consuming, expensive, and difficult process and the conventional approach of regression analysis of stage-discharge relation does not provide encouraging results especially during the floods. P

Optimal Decision Tree Based Multi-class Support Vector Machine

Landslide Susceptibility Assessment in Vietnam Using Support Vector Machines, Decision Tree, and Naı̈ve Bayes Models

1 Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, P.O. Box 5003IMT, 1432 Aas, Norway 2 Faculty of Surveying and Mapping, Hanoi University of Mining and Geology, Dong Ngac, Tu Liem, Hanoi, Vietnam 3 Department of Civil Engineering, Spatial and Numerical Modelling Research Group, Faculty of Engineering, Universiti Putra Malaysia, Selangor, 43400 Serdang,...