In this paper the complicated task of educational software evaluation is revisited and examined from a different point of view. By the means of Educational Data Mining (EDM) techniques, in the present study 177 of the most common evaluation standards that have been proposed by various researchers are examined and evaluated with regards to the degree they affect the effectiveness of educational ...

Teaching and Learning process of an educational institution needs to be monitored and effectively analysed for enhancement. Teaching and Learning is a vital element for an educational institution. It is also one of the criteria set by majority of the Accreditation Agencies around the world. Learning analytics and Educational Data Mining are relatively new. Learning analytics refers to the colle...

Data mining is an instance of the inductive methodology. Many philosophical considerations for induction can also be carried out for data mining. In particular, the justification of induction has been a long-standing problem in epistemology. This article is a recast of the problem in the context of data mining. We formulate the problem precisely in the rough set-based decision logic and discuss...

Feature selection methods for mining bioinformatics data – p. 1/3

A very important problem in the data mining process is detecting too late that the tool selected is inappropriate to do the objective of business. If this happens, we are wasting time and money. This paper presents a methodology that permits to select a tool for the process of data mining from a set of characteristics.

Bishop(2) establishes that in practical applications of data mining, the choice of preprocessing of the available data will be one of the most significant factors in determining the performance of the final system. Data mining situations are often caracterized with the availability of a large number of raw input input variables, sometimes in the tens of thousands range, and comparably few train...

Once it is decided that investment is to be made in the stock, the obvious question which arises is: which all stocks should be purchased? Past performance will not guarantee the future, but it is still worthwhile to evaluate the investments based on their ability to deliver consistent returns with minimal risk. Therefore, the ability to generate most profitable return from short term stock tra...

Auditor selection can be regarded as a matter of audit quality. Research studies aiming to model the auditor choice employ statistical techniques. Here we employ three techniques derived from the Data Mining domain to build models capable of discriminating cases where companies choose a Big 4 or a Non-Big 4 auditor. Significant factors associated with the auditor choice are revealed. The three ...

Recommending appropriate classification algorithm for given new dataset is very important and useful task but also is full of challenges. According to NO-FREE-LUNCH theorem, there is no best classifier for different classification problems. It is difficult to predict which learning algorithm will work best for what type of data and domain. In this paper, a method of recommending classification ...

Data Mining tools extract knowledge from large databases. The data generated in manufacturing has not been entirely exploited. This chapter discusses applications of Data Mining in a manufacturing environment. A methodology for selection of manufacturing processes is proposed and illustrated with an industrial scenario.