Outputs (6)

A Measure of Structural Complexity of Hierarchical Fuzzy Systems Adapted from Software Engineering (2019)
Presentation / Conference Contribution
Razak, T. R., Garibaldi, J. M., & Wagner, C. (2019, June). A Measure of Structural Complexity of Hierarchical Fuzzy Systems Adapted from Software Engineering. Presented at International Conference on Fuzzy Systems (FUZZ-IEEE 2019), New Orleans, USA

Hierarchical fuzzy systems (HFSs) have been seen as an effective approach to reduce the complexity of fuzzy logic systems (FLSs), largely as a result of reducing the number of rules. However, it is not clear completely how complexity of HFSs can be m... Read More about A Measure of Structural Complexity of Hierarchical Fuzzy Systems Adapted from Software Engineering.

Fuzzy Integral Driven Ensemble Classification using A Priori Fuzzy Measures (2019)
Presentation / Conference Contribution
Agrawal, U., Wagner, C., Garibaldi, J. M., & Soria, D. (2019, June). Fuzzy Integral Driven Ensemble Classification using A Priori Fuzzy Measures. Presented at 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), New Orleans, LA, USA

Aggregation operators are mathematical functions that enable the fusion of information from multiple sources. Fuzzy Integrals (FIs) are widely used aggregation operators, which combine information in respect to a Fuzzy Measure (FM) which captures the... Read More about Fuzzy Integral Driven Ensemble Classification using A Priori Fuzzy Measures.

Measuring Inter-group Agreement on zSlice Based General Type-2 Fuzzy Sets (2019)
Presentation / Conference Contribution
Navarro, J., & Wagner, C. (2019, June). Measuring Inter-group Agreement on zSlice Based General Type-2 Fuzzy Sets. Presented at 2019 IEEE International Conference on Fuzzy Systems, New Orleans, Lousiana, USA

Recently, there has been much research into modelling of uncertainty in human perception through Fuzzy Sets (FSs). Most of this research has focused on allowing respondents to express their (intra) uncertainty using intervals. Here, depending on the... Read More about Measuring Inter-group Agreement on zSlice Based General Type-2 Fuzzy Sets.

Paid Crowdsourcing, Low Income Contributors, and Subjectivity (2019)
Book Chapter
Haralabopoulos, G., Wagner, C., McAuley, D., & Anagnostopoulos, I. (2019). Paid Crowdsourcing, Low Income Contributors, and Subjectivity. In I. Maglogiannis, J. MacIntyre, L. Iliadis, & E. Pimenidis (Eds.), Artificial Intelligence Applications and Innovations: AIAI 2019 IFIP WG 12.5 International Workshops: MHDW and 5G-PINE 2019, Hersonissos, Crete, Greece, May 24–26, 2019, Proceedings (225-231). Springer Verlag. https://doi.org/10.1007/978-3-030-19909-8_20

Scientific projects that require human computation often resort to crowdsourcing. Interested individuals can contribute to a crowdsourcing task, essentially contributing towards the project's goals. To motivate participation and engagement, scientist... Read More about Paid Crowdsourcing, Low Income Contributors, and Subjectivity.

Combining clustering and classification ensembles: A novel pipeline to identify breast cancer profiles (2019)
Journal Article
Agrawal, U., Soria, D., Wagner, C., Garibaldi, J., Ellis, I. O., Bartlett, J. M. S., Cameron, D., Rakha, E. A., & Green, A. R. (2019). Combining clustering and classification ensembles: A novel pipeline to identify breast cancer profiles. Artificial Intelligence in Medicine, 97, 27-37. https://doi.org/10.1016/j.artmed.2019.05.002

Breast Cancer is one of the most common causes of cancer death in women, representing a very complex disease with varied molecular alterations. To assist breast cancer prognosis, the classification of patients into biological groups is of great signi... Read More about Combining clustering and classification ensembles: A novel pipeline to identify breast cancer profiles.

Measuring similarity between discontinuous intervals : challenges and solutions (2019)
Presentation / Conference Contribution
Kabir, S., Wagner, C., Havens, T. C., & Anderson, D. T. (2019, June). Measuring similarity between discontinuous intervals : challenges and solutions. Presented at 2019 IEEE Conference on Fuzzy Systems, New Orleans, Louisiana, USA

Discontinuous intervals (DIs) arise in a wide range of contexts, from real world data capture of human opinion to α-cuts of non-convex fuzzy sets. Commonly, for assessing the similarity of DIs, the latter are converted into their continuous form, fol... Read More about Measuring similarity between discontinuous intervals : challenges and solutions.