: The performances of Normalised RBF (NRBF) nets and standard RBF nets are compared in simple classification and mapping problems. In Normalized RBF networks, the traditional roles...
In multi-instance learning, the training examples are bags composed of instances without labels, and the task is to predict the labels of unseen bags through analyzing the training...
Different features have different relevance to a particular learning problem. Some features are less relevant; while some very important. Instead of selecting the most relevant fe...
—Normalization before clustering is often needed for proximity indices, such as Euclidian distance, which are sensitive to differences in the magnitude or scales of the attribute...
Novelty detection in time series is an important problem with application in different domains such as machine failure detection, fraud detection and auditing. An approach to this...
Adriano L. I. Oliveira, Fernando Buarque de Lima N...