Identifying customers who are more likely to respond to a product offering is an important
issue in direct marketing. In direct marketing, data mining has been used extensively to …

To survive in the highly competitive global economy, manufacturing systems must be able to
adapt to new circumstances. An important prerequisite for adaptation is the ability to learn, a …

A lot of time is spent searching for the most performing data mining algorithms applied in
clinical diagnosis. The study set out to identify the most performing predictive data mining …

This paper focused on the development of a predictive model for the classification of the risk
of kidney stones in Nigerian using data mining techniques based on historical information …

The paper addresses some theoretical and practical aspects of data mining, focusing on
predictive data mining, where two central types of prediction problems are discussed …

La delincuencia es un problema que persiste en las ciudades modernas, y en concreto este
TFG se centrará en los sucesos de tiroteos en la ciudad de Nueva York, con la finalidad de …

In order to generate meaningful information from the large datasets, mining algorithms have
been used. Mining algorithms are used to abstract the unknown pattern from the immense …

Many real-world data sets exhibit imbalanced class distributions in which almost all
instances are assigned to one class and far fewer instances to a smaller, yet usually …

This paper focused on the development of a predictive model for the classification of the risk
of kidney stones in Nigerian using data mining techniques based on historical information …

Predictive analytics plays an important role in the decision-making process and intuitive
business decisions, by overthrowing the traditional instinct process. Predictive analytics …