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...

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...

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...

Experts in finance and accounting select feature subset for corporate financial distress prediction according to their professional understanding of the characteristics of the features, while researchers in data mining often believe that data alone can tell everything and they use various mining techniques to search the feature subset without considering the financial and accounting meanings of...

The Internet has unlimited resources of knowledge and is widely used in many applications. Web mining plays an important role in discovering such knowledge, it is roughly divided into three categories : Web Content Mining , Web Usage Mining and Web Structure Mining. The web consists of imprecise, incomplete and uncertain data and knowledge. Fuzzy Set Theory is often used to handle such data. Se...

In the last years, the class of machine learning algorithms were extended with new techniques as for example, data mining techniques. The purpose of data-mining techniques is to extract valuable implicit regularities contained in large databases. The paper presents an analysis of some data-mining techniques used in the development of a knowledge-based system.

the rapid growing of information technology (it) motivates and makes competitive advantages in health care industry. nowadays, many hospitals try to build a successful customer relationship management (crm) to recognize target and potential patients, increase patient loyalty and satisfaction and finally maximize their profitability. many hospitals have large data warehouses containing customer ...

Data mining plays important role in marketing and is quite new. Although this field expands rapidly, data mining is still foreign issue for many marketers who trust only their experiences. Data mining techniques cannot substitute the significant role of domain experts and their business knowledge. In the other words, data mining algorithms are powerful but cannot effectively work without the ac...