Abstract Machine learning (ML), as the most promising paradigm to discover deep
knowledge from data, has been widely applied to practical applications, such as …

The induction of decision trees is a widely-used approach to build classification models that
guarantee high performance and expressiveness. Since a recursive-partitioning strategy …

The social network, by the name which has popularised in today's world and growing rapidly
at all times and controlling over mankind. The social networks like Twitter, Facebook, and …

The telecoms industry is a highly competitive sector which is constantly challenged by
customer churn or attrition. In order to remain steadfast in the consumer business …

Decision trees are few of the most extensively researched domains in Knowledge Discovery.
Irrespective of such advantages as the ability to explain the choice procedure and low …

This study reports the empirical analysis of a hyper-heuristic evolutionary algorithm that is
capable of automatically designing top-down decision-tree induction algorithms. Top-down …

A CART decision tree algorithm based on attribute weight is proposed in this paper because
of the present problems of complex classification, poor accuracy, low efficiency, and severe …

Software effort prediction is an important task within software engineering. In particular,
machine learning algorithms have been widely-employed to this task, bearing in mind their …

Decision-tree induction algorithms are widely used in knowledge discovery and data mining,
specially in scenarios where model comprehensibility is desired. A variation of the traditional …

Data mining has as goal to discover knowledge from huge volume of data. Rule mining is
considered as one of the usable mining method in order to obtain valuable knowledge from …