advanced data mining techniques can be used in universities classification, discovering specific patterns in the determination of successful students, design of a plan or a teaching method and finding critical points of financial management. in this article, we proposed a method to predict the rate of student enrollment in coming years. the data for this research were from data sets of voluntee...

We introduce a complexity measure for decision trees called the soft rank, which measures how wellbalanced a given tree is. The soft rank is a somehow relaxed variant of the rank. Among all decision trees of depth d, the complete binary decision tree (the most balanced tree) has maximum soft rank d, the decision list (the most unbalanced tree) has minimum soft rank √ d, and any other trees have...

The article presents the extension of a common decision tree concept to a multidimensional - vector - decision tree constructed with the help of evolutionary techniques. In contrary to the common decision tree the vector decision tree can make more than just one suggestion per input sample. It has the functionality of many separate decision trees acting on a same set of training data and answer...

Decision tree classification techniques are currently gaining increasing impact especially in the light of the ongoing growth of data mining services. A central challenge for the decision tree classification is the identification of split rule and correct attributes. In this context, the article aims at presenting the current state of research on different techniques for classification using ob...

Decision tree construction is an important data-mining problem. In this paper we introduce an approach of using cumulative information estimations for fuzzy decision tree induction. We present new type of fuzzy decision tree: ordered tree. This tree is oriented to parallel processing of attributes with differing costs.

Apart from the need for superior accuracy, healthcare applications of intelligent systems also demand deployment interpretable machine learning models which allow clinicians to interrogate and validate extracted medical knowledge. Fuzzy rule-based are generally considered that able reflect associations between conditions associated symptoms, through use linguistic if-then statements. Systems bu...

Searching for a binary partition of attribute domains is an important task in data mining. It is present in both decision tree construction and discretization. The most important advantages of decision tree methods are compactness and clearness of knowledge representation as well as high accuracy of classification. Decision tree algorithms also have some drawbacks. In cases of large data tables...

DEXSY2 is a dental expert system, which diagnoses oral diseases and offers a treatment course. The system which is designed and implemented from scratch is capable of diagnosing among thirty five oral diseases and offering a course of treatment for each. It uses a decision tree for its representation of knowledge, and each of its nodes contains a frame. The knowledge base of the system contains...