TREPAN is decision tree algorithm that utilises artificial neural networks (ANNs) in order to improve partitioning conditions when sample data is sparse. When sample sizes are limited during the tree-induction process, TREPAN relies on an ANN oracle in order to create artificial sample...

This paper explores the experience of two academics commissioned, by a public body engaged in policy formulation, to carry out research to inform the policy process. During the presentation of qualitative data to the public body, one representative exclaimed "it's not true!" The report was...

The major industrial control purpose is the reaching of the expected performances. In this sense, improvement processes are continuously carried out in order to define the right actions with regard to the objectives achievement. Thus, in order to better monitor the performance continuous...

Logistic regression (LR) continues to be one of the most widely used methods in data mining in general and binary data classification in particular. This paper is focused on providing an overview of the most important aspects of LR when used in data analysis, specifically from an algorithmic and...

This paper aims at providing a parameter estimation method for the machine tool reliability analysis to overcome the problem of unavailability of a well-defined failure data collection mechanism. It uses the knowledge and experience of maintenance personnel to obtain the parameters of lifetime...

In this paper, I defined a similarity coefficient, called Rao DISC-based similarity coefficient (DbSC), which takes into consideration feature differences as a factor of measuring similarity. Such coefficient was based from Rao dissimilarity coefficient (DISC) and diversity coefficient (DIVC)...

The evaluation criteria for most marketing and management journals underline the importance of student samples' characteristics and how well they represent the population being studied. However, the predominance of student samples in empirical marketing and management research is sufficient...

This research demonstrates the application of multiple data mining techniques to test theories of the macro-level causes of terrorism. The unique dataset is comprised of terrorist events and measures of social, political and economic contexts in 185 countries worldwide between the years 1970 and...

The method of association rule mining has been used by marketers for many years to extract marketing rules from purchase transactions. Marketers and managers employ these rules in order to predict customer needs for future sales. Extracting effective rules is one of the major problems of...

We present new, tractable methods to impute missing values based on conditional probability density functions that we estimate via copula and mixture models. Our methods exploit known analytical results concerning conditional distributions for the Arellano-Valle and Bolfarine's generalised...