Data mining is much more than simply building statistical models from large collections of data. In particular, this paper records a core task of mining as exploring through the space of models that are built in a data mining project. The idea was first introduced through the concept of multiple inductive learning (MIL) (Williams, 1988, 1991) and further developed in practise as mining the data...

Mental health is an important issue for university students. The objective of this article was to apply and compare the different classification methods students’ mental problems. Furthermore, it presents ensemble method improve accuracy classifiers assist psychologists in decision making process. For this, 10 were applied classifying students into two groups. In addition, combining are p...

Predictive data mining in clinical medicine deals with learning models to predict patients’ health. The models can be devoted to support clinicians in diagnostic, therapeutic, or monitoring tasks. Data mining methods are usually applied in clinical contexts to analyze retrospective data, thus giving healthcare professionals the opportunity to exploit large amounts of data routinely collected du...

Poor academic performance of students is a concern in the educational sector, especially if it leads to being unable meet minimum course requirements. However, with timely prediction students’ performance, educators can detect at-risk students, thereby enabling early interventions for supporting these overcoming their learning difficulties. majority studies have taken approach developing indivi...

to identify important attributes/factors that contribute to grain and biological yields of wheat, 9912 sets of diverse data from field studies were extracted, and supervised attribute-weighting models were employed. results showed that when biological yield was the output, grain yield, nitrogen applied, rainfall, irrigation regime, and organic content were the most important factors/attributes,...

Due to the rapid growth of data mining technology, obtaining private data on users through this technology becomes easier. Association Rules Mining is one of the data mining techniques to extract useful patterns in the form of association rules. One of the main problems in applying this technique on databases is the disclosure of sensitive data by endangering security and privacy. Hiding the as...

the concept of intelligently controlling the search process of gravitational search algorithm (gsa) is introduced to develop a novel data mining technique. the proposed method is called fuzzy gsa miner (fgsa-miner). at first a fuzzy controller is designed for adaptively controlling the gravitational coefficient and the number of effective objects, as two important parameters which play major ro...