In recent years, mining frequent itemsets over uncertain data has attracted much attention in the data mining community. Unlike the corresponding problem in deterministic data, th...
In the last decades, a large family of algorithms supervised or unsupervised; stemming from statistic or geometry theory have been proposed to provide different solutions to the p...
Discovering association rules that identify relationships among sets of items is an important problem in data mining. Finding frequent item sets is computationally the most expens...
This paper presents an extension to genetic programming to allow the evolution of programs containing local variables with static scope which obey the invariant that all variables...
Background: Technological advances in high-throughput techniques and efficient data acquisition methods have resulted in a massive amount of life science data. The data is stored ...