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...

OBJECTIVES The importance of the prediction of coronary heart disease (CHD) has been recognized in Korea; however, few studies have been conducted in this area. Therefore, it is necessary to develop a method for the prediction and classification of CHD in Koreans. METHODS A model for CHD prediction must be designed according to rule-based guidelines. In this study, a fuzzy logic and decision ...

OBJECTIVE To develop a decision tree based on health-related quality of life outcomes rather than expert consensus for determining the appropriateness of total hip replacement (THR) among patients with hip OA. METHODS This is a prospective observational study of two independent cohorts. The derivation cohort included 590 patients recruited from seven hospitals between March 1999 and March 200...

Treemodels are valuable tools for predictivemodeling and datamining. Traditional tree-growingmethodologies such as CART are known to suffer from problems including greediness, instability, and bias in split rule selection. Alternative tree methods, including Bayesian CART (Chipman et al., 1998; Denison et al., 1998), random forests (Breiman, 2001a), bootstrap bumping (Tibshirani and Knight, 199...

Bagian terpenting dalam software quality adalah prediksi cacat software. Prediksi memanfaatkan pengukuran matriks pengujian untuk dilakukan klasifikasi yang dapat memperkirakan kualitas modul program, secara umum hasil dibagi menjadi dua kelas, yaitu rentan dan tidak cacat. Metode machine learning mempunyai kinerja lebih baik menemukan daripada metode manual. Algoritme pernah digunakan antara l...

The study compares the effectiveness of Bayesian networks versus Decision Trees for predicting access to renal transplant waiting list in a French healthcare network. The data set consisted in 809 patients starting renal replacement therapy. The data were randomly divided into a training set (90%) and a validation set (10%). Bayesian network and CART decision tree were built on the training set...

Random forests are a popular classification method based on an ensemble of a single type of decision trees from subspaces of data. In the literature, there are many different types of decision tree algorithms, including C4.5, CART, and CHAID. Each type of decision tree algorithm may capture different information and structure. This paper proposes a hybrid weighted random forest algorithm, simul...

Objective:Predictions of hospital charges for cancer patients are very important, because they provide a basis for allocating medical resources in the hospital and for establishing national medical policies. But previous studies to predict hospital charges were mainly based on statistical analysis, which has used only a small aspect among huge medical data so that the prediction power was limit...

In this issue of Clinical Infectious Diseases, Varma et al. [1] present data from nearly a quarter century of foodborne botulism cases in the Republic of Georgia [1]. The results may provide Georgia with a cost-saving alternative to the management of botulism cases and may offer guidance for those who are preparing plans for mass numbers of casualties due to botulinum intoxication. The authors ...