Deep neural network (DNN) with a complex structure and multiple nonlinear processing
units has achieved great success for feature learning in machinery fault diagnosis. Due to …

Deep neural networks (DNNs) with a complex structure and multiple nonlinear processing
units have achieved great successes for feature learning in image and visualization …

This paper proposes a new approach to produce classification rules based on evolutionary
computation with novel crossover and mutation operators customized for execution on …

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 …

Nature inspired algorithms have become popular for discovering classification rules due to
their ability to effectively handle large and complex search spaces. However, nature inspired …

Data mining algorithms produce information of a statistical nature that contains accurate and
reliable knowledge. However, in many cases these algorithms do not discover hidden facts …

ABSTRACT Classification Rule Mining (CRM) is a data mining technique for discovering
important classification rules from large dataset. This work presents an efficient genetic …

One of the challenges of data mining is revealing the interesting if-then rules in the mined
dataset. We present two methods for the automated discovery of unexpected, and, thereby …

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 …

Automated discovery of rules is, due to its applicability, one of the most fundamental and
important method in Knowledge Discovery in Databases (KDD). It has been an active …