this paper presents a comprehensive review of the works done, during the 2000–2012, in the application of data mining techniques in credit scoring. yet there isn’t any literature in the field of data mining applications in credit scoring. using a novel research approach, this paper investigates academic and systematic literature review and includes all of the journals in the science direct onli...

background: selecting the correct statistical test and data mining method depends highly on the measurement scale of data, type of variables, and purpose of the analysis. different measurement scales are studied in details and statistical comparison, modeling, and data mining methods are studied based upon using several medical examples. we have presented two ordinal–variables clustering exampl...

patients and methods in this cross-sectional study, data of 584 female patients (mean age of 45.9 years) referred to breast cancer research center (tehran, iran) were analyzed anonymously. spss and norm softwares (2.03) were used for data transformation, running and interpretation of cca and replacing missing values, respectively. data were obtained from breast cancer research center, tehran, i...

fuzzy cognitive maps (fcms) have successfully been applied in numerous domains to show the relations between essential components in complex systems. in this paper, a novel learning method is proposed to construct fcms based on historical data and by using meta-heuristic: genetic algorithm (ga), simulated annealing (sa), and tabu search (ts). implementation of the proposed method has demonstrat...

in today’s quality- based competitive world, known as knowledge age, customer attraction is of ultimate importance. in respect to the slogan “customer is always right”, customer relation management is the core of an organizational strategy playing an important role in four aspects of customer identification, customer attraction, customer retaining, and customer satisfaction. commercial organiza...

introduction: the aim of this study was to determine the performance of data mining techniques for predicting the causes of traumatic brain injuries in khatamolanbya hospital, zahdan city. method: in this cross–sectional, the study population included all patients who died of brain injury. data were collected by the use of a researcher- made check list, provided under the direct observation of ...

basically, medical diagnosis problems are the most effective component of treatment policies. recently, significant advances have been formed in medical diagnosis fields using data mining techniques. data mining or knowledge discovery is searching large databases to discover patterns and evaluate the probability of next occurrences. in this paper, bayesian classifier is used as a non-linear dat...

conclusions our study showed that arm is a useful approach in determining which combinations of variables or predictors occur together frequently, in people who will develop diabetes. the arm focuses on joint exposure to different combinations of risk factors, and not the predictors alone. background type 2 diabetes, common and serious global health concern, had an estimated worldwide prevalenc...

background : data mining has an interdisciplinary field including various scientific disciplines such as: database systems, statistics, machine learning, artificial intelligence and the others. in the field of medical, data mining algorithms can help physicians to diagnose diseases and chose the best type of treatment. hepatocellular carcinoma has the most common type of liver cancer. given the...