__________________________________________________________________________________________ Abstract: Data mining is method of maintaining a large amount of data stored in the database. Decision tree is a technique of data mining which classify the data and produces valuable results. These results are used in analysis and future prediction. The prime objective of this research work is to present...

Background: Length of stay is one of the most important indicators in assessing hospital performance. A shorter stay can reduce the costs per discharge and shift care from inpatient to less expensive post-acute settings. It can lead to a greater readmission rate, better resource management, and more efficient services. Objective: This study aimed to ident...

Introduction: Lack of a proper method for early detection and diagnostic errors in medicine are some fundamental problems in treating cancer. Data analysis techniques may significantly help early diagnosis. The current study aimed at applying and evaluating neural networks and decision tree algorithm on breast cancer patients’ data for early cancer prediction. Methods: In the current stu...

Introduction: Lack of a proper method for early detection and diagnostic errors in medicine are some fundamental problems in treating cancer. Data analysis techniques may significantly help early diagnosis. The current study aimed at applying and evaluating neural networks and decision tree algorithm on breast cancer patients’ data for early cancer prediction. Methods: In the current stu...

Background: Screening and counselling is the most effective way to prevent the birth of children with thalassemia major. An accurate and relatively less time-consuming protocol is necessary to screen large populations. Separating iron deficiency anaemia from thalassemia trait based on blood cell parameters has been used by hematologists for many years. We aimed to design a new approach to scree...

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...