The paper addresses the problem of distinguishing between pornographic and non-pornographic photographs, for the design of semantic filters for the web. Both, decision forests of trees built according to CART (Classification And Regression Trees) methodology and Support Vectors Machines (SVM), have been used to perform the classification. The photographs are described by a set of low-level feat...

When intense redaction is needed to protect data subjects’ confidentiality, statistical agencies can release synthetic data, in which identifying or sensitive values are replaced with draws from statistical models estimated from the confidential data. Specifying accurate synthesis models can be a difficult and labor intensive task with standard parametric approaches. We describe and empirically...

According to the forensic statistics, in Iran, 26 percent of those killed in traffic accidents are motorcyclists in recent years. Thus, it is necessary to investigate the causes of motorcycle accidents because of the high number of motorcyclist casualties. Motorcyclists' dangerous behaviors are among the causes of events that are discussed in this study. Traffic signs have the important role of...

congenital heart disease is the most common birth defect. The article describes detection and classification of congenital heart defect using classification and regressing trees. The ultimate goal of this research can decrease risk of cardiac arrest and mortality in compared with healthy children. The intelligent system proposed in three stages technique for automate diagnosis:(i) pre-processin...

The objective of this study is to apply ENVISAT MERIS data in mapping mountain vegetation in Sweden. The Swedish mountain vegetation is characterized by mosaics of different land cover types; a single MERIS pixel (300 meter IFOV) can consist of several of these different land cover types. “Hard” classifications which produce a single thematic class per pixel often give a low accuracy. While man...

Classification and Regression Trees (CARTs) are off-the-shelf techniques in modern Statistics Machine Learning. CARTs traditionally built by means of a greedy procedure, sequentially deciding the splitting predictor variable(s) associated threshold. This approach trains trees very fast, but, its nature, their classification accuracy may not be competitive against other state-of-the-art procedur...