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Most of the work in machine learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem of learning when the class-probability distribution that generate the examples changes over time. We present a method for detection of changes in the probability distribution of examples.… (More)

- João Gama, Gladys Castillo
- ADMA
- 2006

Most of the work in Machine Learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem of learning when the distribution that generates the examples changes over time. We present a method for detection of changes in the probability distribution of examples. The idea behind… (More)

- Cristina Carmona, Gladys Castillo, Eva Millán
- ICALT
- 2008

- Gladys Castillo, Eva Millán, Luís Descalço, Paula Oliveira, Sandra Diogo
- Computers & Education
- 2013

- Brigida Monica Faria, Luis Paulo Reis, Nuno Lau, Gladys Castillo
- 2010 IEEE Conference on Cybernetics and…
- 2010

Machine Learning (ML) and Knowledge Discovery (KD) are research areas with several different applications but that share a common objective of acquiring more and new information from data. This paper presents an application of several ML techniques in the identification of the opponent team and also on the classification of robotic soccer formations in the… (More)

- João Gama, Gladys Castillo
- IBERAMIA
- 2002

- Gladys Castillo
- AI Commun.
- 2008

This thesis is concerned with adaptive learning algorithms for Bayesian network classifiers (BNCs) in a prequential (on-line) learning scenario. Online learning is particular relevant since in many applications learning algorithms act in environments where the data flows continuously. An efficient supervised learning algorithm in dynamic environments must… (More)

This chapter presents an adaptive predictive model for a student modeling prediction task in the context of an adaptive educational hypermedia system (AEHS). The task, that consists in determining what kind of learning resources are more appropriate to a particular learning style, presents two issues that are critical. The first is related to the… (More)

- José M. Carmona-Cejudo, Gladys Castillo, Manuel Baena-García, Rafael Morales Bueno
- Knowl.-Based Syst.
- 2013

0950-7051/$ see front matter 2013 Elsevier B.V. A http://dx.doi.org/10.1016/j.knosys.2013.03.006 ⇑ Corresponding author. Address: ETS Ingeniería In nos, 29071 Málaga, Spain. Tel.: +34 952132863; fax: E-mail address: jmcarmona@lcc.uma.es (J.M. Carm Email foldering is a challenging problem mainly due to its high dimensionality and dynamic nature. This work… (More)

- Gladys Castillo, João Gama, Pedro Medas
- EPIA
- 2003

Most of supervised learning algorithms assume the stability of the target concept over time. Nevertheless in many real-user modeling systems, where the data is collected over an extended period of time, the learning task can be complicated by changes in the distribution underlying the data. This problem is known in machine learning as concept drift. The… (More)