Pattern recognition and classification are two of the key topics in computer science. In this
paper a novel method for the task of pattern classification is presented. The proposed …

In this paper the Naïve Associative Classifier (NAC), a novel supervised learning model, is
presented. Its strengths lie in its simplicity, transparency, transportability and accuracy. The …

The paper describes a novel associative model for time series data mining. The model is
based on the Gamma classifier, which is inspired on the Alpha–Beta associative memories …

The current paper contains the theoretical foundation for the off-the-mainstream model
known as Alpha-Beta associative memories (α β α β model). This is an unconventional …

Nowadays, we are immersed in the social and mobile networks era. As a positive
consequence of this, collaborative and mobile learning in educational environments have …

This paper describes different models which are used for forecasting in the time series
context of petroleum engineering. The objective is to reproduce and further predict future oil …

This paper presents an effective method to improve some of the parameters in an
associative classifier, thus increasing its performance. This is accomplished using the …

One of the four basic machine learning tasks is pattern classification. The selection of the
proper learning algorithm for a given problem is a challenging task, formally known as the …

The ever increasing data generation confronts us with the problem of handling online
massive amounts of information. One of the biggest challenges is how to extract valuable …

Software project planning includes as one of its main activities software development effort
prediction (SDEP). Effort (measured in person-hours) is useful to budget and bidding the …