The learning process of a multilayer perceptron requires the optimization of an error function
E (y, t) comparing the predicted output, y, and the observed target, t. We review some usual …

Data Mining for Business Applications presents the state-of-the-art research and
development outcomes on methodologies, techniques, approaches and successful …

The evolution of wireless handsets from simple mobile phones to smart devices, capable of
capturing multimedia information and accessing Internet, has enabled its users to share …

Classification has been widely studied and successfully employed in various application
domains. In multidimensional noisy settings, however, classification accuracy may be …

The principle of minimum error-entropy-MEE-has been recently proposed as a new learning
paradigm, where a measure of error entropy is used as risk functional. This principle can be …

The last years have witnessed an increasing attention to entropy based criteria in adaptive
systems. Several principles were proposed based on the maximization or minimization of …

In this chapter, we focus on eliminating the dimensionality bias. We give a formal definition
of dimensionality bias and analyze consequences for subspace clustering. A new density …