Classifiers are traditionally learned using sets of positive and negative training examples. However, often a classifier is required, but for training only an incomplete set of pos...
The Internet is full of information sources providing various types of data from weather forecasts to travel deals. These sources can be accessed via web-forms, Web Services or RS...
Learning Bayesian networks from data is an N-P hard problem with important practical applications. Several researchers have designed algorithms to overcome the computational comple...
: Phylogenetic profiles of proteins strings of ones and zeros encoding respectively the presence and absence of proteins in a group of genomes have recently been used to id...
Fold recognition is a key problem in computational biology that involves classifying protein sharing structural similarities into classes commonly known as "folds". Rece...