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LAIM discretization for multi-label data
(2017)
Multi-label learning is a challenging task in data mining which has attracted growing attention in recent years. Despite the fact that many multi-label datasets have continuous features, general algorithms developed specially ...
Reducing gaps in quantitative association rules: A genetic programming free-parameter algorithm
(IOS Press, 2014)
The extraction of useful information for decision making is a challenge in many different domains. Association rule mining is one of the most important techniques in this field, discovering relationships of interest among ...
An Automatic Programming ACO-Based Algorithm for Classification Rule Mining
(2017-01-20)
In this paper we present a novel algorithm, named GBAP, that jointly uses
automatic programming with ant colony optimization for mining classification rules.
GBAP is based on a context-free grammar that properly guides ...
JCLEC Meets WEKA!
(2014-02-27)
WEKA has recently become a very referenced DM tool. In
spite of all the functionality it provides, it does not include any framework
for the development of evolutionary algorithms. An evolutionary
computation framework ...
A Classification Module for Genetic Programming Algorithms in JCLEC
(MIT Press, 2014)
JCLEC-Classi cation is a usable and extensible open source library for genetic program-
ming classi cation algorithms. It houses implementations of rule-based methods for clas-
si cation based on genetic programming, ...
Subgroup Discovery in MOOCs: A Big Data Application for Describing Different Types of Learners
(Taylor & Francis, 2019)
The aim of this paper is to categorize and describe di erent types of learners in mas-
sive open online courses (MOOCs) by means of a subgroup discovery approach based
on MapReduce. The nal objective is to discover ...