All Outputs (5)

Ensemble selection based on classifier prediction confidence. (2019)
Journal Article
NGUYEN, T.T., LUONG, A.V., DANG, M.T., LIEW, A.W.-C. and MCCALL, J. 2020. Ensemble selection based on classifier prediction confidence. Pattern recognition [online], 100, article ID 107104. Available from: https://doi.org/10.1016/j.patcog.2019.107104

Ensemble selection is one of the most studied topics in ensemble learning because a selected subset of base classifiers may perform better than the whole ensemble system. In recent years, a great many ensemble selection methods have been introduced.... Read More about Ensemble selection based on classifier prediction confidence..

Multi-label classification via incremental clustering on an evolving data stream. (2019)
Journal Article
NGUYEN, T.T., DANG, M.T., LUONG, A.V., LIEW, A. W.-C., LIANG, T. and MCCALL, J. 2019. Multi-label classification via incremental clustering on an evolving data stream. Pattern recognition [online], 95, pages 96-113. Available from: https://doi.org/10.1016/j.patcog.2019.06.001

With the advancement of storage and processing technology, an enormous amount of data is collected on a daily basis in many applications. Nowadays, advanced data analytics have been used to mine the collected data for useful information and make pred... Read More about Multi-label classification via incremental clustering on an evolving data stream..

A weighted multiple classifier framework based on random projection. (2019)
Journal Article
NGUYEN, T.T., DANG, M.T., LIEW, A. W.-C. and BEZDEK, J.C. 2019. A weighted multiple classifier framework based on random projection. Information science [online], 490, pages 36-58. Available from: https://doi.org/10.1016/j.ins.2019.03.067

In this paper, we propose a weighted multiple classifier framework based on random projections. Similar to the mechanism of other homogeneous ensemble methods, the base classifiers in our approach are obtained by a learning algorithm on different tra... Read More about A weighted multiple classifier framework based on random projection..

A lossless online Bayesian classifier. (2019)
Journal Article
NGUYEN, T.T.T., NGUYEN, T.T., SHARMA, R. and LIEW, A. W.-C. 2019. A lossless online Bayesian classifier. Information sciences [online], 489, pages 1-17. Available from: https://doi.org/10.1016/j.ins.2019.03.031

We are living in a world progressively driven by data. Besides the issue that big data cannot be entirely stored in the main memory as required by traditional offline learning methods, the problem of learning data that can only be collected over time... Read More about A lossless online Bayesian classifier..

Multi-label classification via label correlation and first order feature dependance in a data stream. (2019)
Journal Article
NGUYEN, T.T., NGUYEN, T.T.T., LUONG, A.V., NGUYEN, Q.V.H., LIEW, A.W.-C. and STANTIC, B. 2019. Multi-label classification via label correlation and first order feature dependance in a data stream. Pattern recognition [online], 90, pages 35-51. Available from: https://doi.org/10.1016/j.patcog.2019.01.007

Many batch learning algorithms have been introduced for offline multi-label classification (MLC) over the years. However, the increasing data volume in many applications such as social networks, sensor networks, and traffic monitoring has posed many... Read More about Multi-label classification via label correlation and first order feature dependance in a data stream..