Classification and regression trees (CART) are convenient for low complexity speaker recognition on embedded devices. However, former attempts at using trees performed quite poorly compared to state of the art results with Gaussian Mixture Models (GMM). In this article, we introduce some solutions to improve the efficiency of the tree-based approach. First, we propose to use at the tree constru...

Land cover mapping provides basic information for advanced science such as ecological management, biodiversity conservation, forest planning and so on. In remote sensing research, the process of creating an accurate land cover map is an important subject. Recently, there has been growing research interest in the object-oriented image classification techniques. The object-oriented image classifi...

Deriving predictive models in medicine typically relies on a population approach where a single model is developed from a dataset of individuals. In this paper we describe and evaluate a personalized approach in which we construct a new type of decision tree model called decision-path model that takes advantage of the particular features of a given person of interest. We introduce three persona...

BACKGROUND Incidence of liver hydatid cyst (LHC) rupture ranged 15%-40% of all cases and most of them concern the bile duct tree. Patients with biliocystic communication (BCC) had specific clinic and therapeutic aspect. The purpose of this study was to determine witch patients with LHC may develop BCC using classification and regression tree (CART) analysis METHODS A retrospective study of 67...

ÐA fuzzy decision tree is constructed by allowing the possibility of partial membership of a point in the nodes that make up the tree structure. This extension of its expressive capabilities transforms the decision tree into a powerful functional approximant that incorporates features of connectionist methods, while remaining easily interpretable. Fuzzification is achieved by superimposing a fu...

Storage device performance prediction is a key element of self-managed storage systems and application planning tasks, such as data assignment and configuration. Based on bagging ensemble, we proposed an algorithm named selective bagging classification and regression tree (SBCART) to model storage device performance. It can improve the accuracy of a single CART model. In contrast with CART mode...

To discriminate between breast cancer patients and controls, we used a three-step approach to obtain our decision rule. First, we ranked the mass/charge values using random forests, because it generates importance indices that take possible interactions into account. We observed that the top ranked variables consisted of highly correlated contiguous mass/charge values, which were grouped in the...

OBJECTIVES In this paper three statistical methods [logistic regression, classification and regression tree (CART), and fuzzy inference] for the prediction of lymph node metastasis in carcinoma of the tongue are compared. METHODS A retrospective collection of data in 75 patients treated for tongue cancer was carried out at the Clinic and Policlinic for Oral and Maxillo-facial Surgery at the U...

The prediction of accurate segmental durations remains a difficult problem when synthesising speech from text. Inaccurate durations are often perceptually prominent and detract from the naturalness of the quality of speech. For a concatenative system, a statistical approach is an excellent way of predicting segmental durations. More specifically a CART (Classification And Regression Tree) metho...