Classification is an important data mining task which facilitates list of decision rules that
helps us to predict class of an unseen instance. Various traditional techniques like Decision …

Feature selection is a pre-processing technique in which a subset or a small number of
features, which are relevant and non-redundant, are selected for better classification …

Ant colony optimisation (ACO) algorithms have been used to discover accurate, and
comprehensible classification rules. Discovering exceptions using ACO is an underexplored …

Knowledge discovery in databases (KDD) has received great progress in recent years for
the need of mining useful knowledge in the ever growing information. The advances in …

O atual momento da tecnologia vem promovendo meios para o aumento exponencial no
volume de informações disponíveis na internet ou em organizações. Considerando que …

Objective. Support decision making when choosing the most appropriate technique for the
development of a data mining project. Materials and methods. Association and logistic …

One of the vital areas of attention in the field of knowledge discovery is to analyze the
interestingness measures in rule discovery and to select the best one according to the …

The discovery of knowledge in textual databases is an approach that basically seeks for
implicit relationships between different concepts in different documents written in natural …

Data Stream mining is the process of digging out knowledge from the uninterrupted streams
of data. Unlike to previously known data, stream based data are huge in size and change or …

Decision tree algorithms, being accurate and comprehensible classifiers, have been one of
the most widely used classifiers in data mining and machine learning. However, like many …