This study developed a depression prediction model for female students from multicultural families by using a decision tree model based on Chi-squared automatic interaction detection (CHAID) algorithm. Subjects of the study were 9,024 female students between 12 and 15 years old among the children of surveyed marriage immigrants. Outcome variables were classified as presence of depression. Expla...

The purpose of this study is to determine new prognostic indexes for the differentiation of subgroups of breast cancer patients with the techniques of decision tree algorithms (C&RT, CHAID, QUEST, ID3, C4.5 and C5.0) and Cox regression analysis for disease-free survival (DFS) in breast cancer patients. A retrospective analysis was performed in 381 breast cancer patients diagnosed. Age, menopaus...

BACKGROUND The Dog erythrocyte antigen (DEA) 1 blood group system was thought to contain types DEA 1.1 and 1.2 (and possibly 1.3 [A3]). However, DEA 1.2+ dogs are very rare and newer typing methods reveal varying degrees of DEA 1 positivity. OBJECTIVES To assess if variation in DEA 1 positivity is because of quantitative differences in surface antigen expression. To determine expression patte...

The aim of this paper is twofold. First we discuss the origin of tree methods. Essentially we survey earlier methods that led to CHAID (Kass, 1980; Biggs et al., 1991). The second goal is then to explain in details the functioning of CHAID, especially the differences between the original method as described in Kass (1980) and the nowadays currently implemented extension that was proposed by Big...

This paper proposes a decision treemodel for specifying the importance of 21 factors causing the landslides in a wide area of Penang Island, Malaysia. These factors are vegetation cover, distance from the fault line, slope angle, cross curvature, slope aspect, distance from road, geology, diagonal length, longitude curvature, rugosity, plan curvature, elevation, rain perception, soil texture, s...

With this research, we sought to examine the performance of six different regression tree data mining methods to predict mortality in head injury. Using a data set consisting of 1603 head injury cases, we assessed the performance of: the Classification and Regression Trees (CART) method; the Chi-squared Automatic Interaction Detector (CHAID) method; the Exhaustive CHAID (E-CHAID) method; the Qu...

The objective of this paper is to develop a model for ECG (electrocardiogram) classification based on Data Mining techniques. The MITBIH Arrhythmia database was used for ECG classical features analysis. This work is divided into two important parts. The first parts deals with extraction and automatic analysis for different waves of electrocardiogram by time domain analysis and the second one co...

The purpose of this study is to construct a valid and rigorous fraudulent financial statement detection model. The research objects are companies which experienced both fraudulent and non-fraudulent financial statements between the years 2002 and 2013. In the first stage, two decision tree algorithms, including the classification and regression trees (CART) and the Chi squared automatic interac...

This research presents a new application of Data Envelopment Analysis (DEA) to empirically determine prices of multiple products. The DEA technique is now widely applied to performance analysis and efficiency measurement in economics, business and other areas in social science. This study does not explore such conventional DEA uses, rather directing towards a new DEA application to the determin...

This paper proposes a new efficiency benchmarking methodology that is capable of incorporating probability while still preserving the advantages of a distribution-free and nonparametric modeling technique. This new technique developed in this paper will be known as the DEA-Chebyshev model. The foundation of DEA-Chebyshev model is based on the model pioneered by Charnes, Cooper, and Rhodes in 19...