Instance selection plays an important role in improving scalability of data mining algorithms, but it can also be used to improve the quality of the data mining results. In this dissertation we present a new optimization-based approach for instance selection that uses a genetic algorithm (GA) to select a subset of instances to produce a simpler decision tree with acceptable accuracy. The result...

Over the years, various methodologies have been investigated and proposed to deal with continuous or numeric data which is very common in any application. With the increasing popularity of fuzzy representation, researchers have proposed to utilize fuzzy logic in decision trees to deal with the situations. This paper presents a survey of current methodology to design FDT (Fuzzy Decision Tree), v...

background non-alcoholic fatty liver disease (nafld) is the most common form of liver disease in many parts of the world. objectives the aim of the present study was to identify the most important factors influencing nafld using a classification tree (ct) to predict the probability of nafld. patients and methods this cross-sectional study was conducted in kavar, a town in the south of fars prov...

Decision tree classification technique is one of the most popular techniques in the emerging field of data mining. There are various methods for constructing decision tree. Induced Decision tree (ID3) is the basic algorithm for constructing decision trees. After ID3 various algorithms were proposed by different researchers and authors those are extensions of ID3 algorithm. This paper contains a...