Understanding and forecasting urban Air Quality (AQ) is not only a multifaceted and computationally challenging problem for machine learning algorithms, but also a difficult task for human-decision makers: the strict regulatory framework, in combination with the public demand for better information services poses the need for robust, efficient and, more importantly, understandable forecasting m...

This paper explores the effectiveness of Data Mining (DM) classification techniques in detecting firms that issue fraudulent financial statements (FFS) and deals with the identification of factors associated to FFS. In accomplishing the task of management fraud detection, auditors could be facilitated in their work by using Data Mining techniques. This study investigates the usefulness of Decis...

prolactin is mainly secreted by the anterior pituitary and is able to stimulate mammary gland development and lactation in mammalians. although prolactins share a common ancestral gene encoding, they show species specific characteristics and their efficiency may be different in various mammals. the importance of protein structures of all sequences of this hormone have been studied by various bi...

In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). Bayesian approaches are a fundamentally important DM technique. Given the probability distribution, Bayes classifier can provably achie...

In this paper, we define the SMARTBASEG architecture and show the preliminary results we have obtained in some experiments. Our proposal considers that the domain of Data Mining (DM) can be represented in terms of an ontology containing the definition of the main concepts involved in its algorithms. We also use ontology to describe some characteristics of a computational grid. This declarative ...

Like model selection in statistics, the choice of appropriate Data Mining Algorithms (DM-Algorithms) is a very important task in the process of Knowledge Discovery. Due to this fact it is necessary to have sophisticated metrics that can be used as comparators to evaluate alternative DMalgorithms. It has been shown in literature, that Data Envelopment Analysis (DEA) is an appropriate platform to...

The increasingly vast number of marketing campaigns over time has reduced its effect on the general public. Furthermore, economical pressures and competition has led marketing managers to invest on directed campaigns with a strict and rigorous selection of contacts. Such direct campaigns can be enhanced through the use of Business Intelligence (BI) and Data Mining (DM) techniques. This paper de...

background and purpose: kidney failure reduces the kidney function and in long term it leads to chronic kidney disease. one of the main complications of this disease is irreversible damage to the kidneys (end-stage kidney disease) and hemodialysis is the main method used to treat advanced kidney failure. the main problem associated with hemodialysis is treating anemia caused by lack of erythrop...

abstract precipitation is an important variable which is used in definition of drought. based on precipitation amounts, some indices are devised for drought monitoring including, the standardized precipitation index (spi) and the standard index of annual precipitation (siap). each of these drought indices are classified into some classes so that each class descripts a given severity of drought....