All Outputs (7)

Handling uncertainty in citizen science data: towards an improved amateur-based large-scale classification (2018)
Journal Article
Jiménez, M., Triguero, I., & John, R. (2019). Handling uncertainty in citizen science data: towards an improved amateur-based large-scale classification. Information Sciences, 479, 301-320. https://doi.org/10.1016/j.ins.2018.12.011

© 2018 Citizen Science, traditionally known as the engagement of amateur participants in research, is showing great potential for large-scale processing of data. In areas such as astronomy, biology, or geo-sciences, where emerging technologies genera... Read More about Handling uncertainty in citizen science data: towards an improved amateur-based large-scale classification.

A preliminary study on Hybrid Spill-Tree Fuzzy k-Nearest Neighbors for big data classification (2018)
Conference Proceeding
Maillo, J., Luengo, J., Garcia, S., Herrera, F., & Triguero, I. (2018). A preliminary study on Hybrid Spill-Tree Fuzzy k-Nearest Neighbors for big data classification. In 2018 IEEE International Conference on Fuzzy Systems (FUXX-IEEE) (1-8). https://doi.org/10.1109/FUZZ-IEEE.2018.8491595

The Fuzzy k Nearest Neighbor (Fuzzy kNN) classifier is well known for its effectiveness in supervised learning problems. kNN classifies by comparing new incoming examples with a similarity function using the samples of the training set. The fuzzy ver... Read More about A preliminary study on Hybrid Spill-Tree Fuzzy k-Nearest Neighbors for big data classification.

Coevolutionary fuzzy attribute order reduction with complete attribute-value space tree (2018)
Journal Article
Ding, W., Triguero, I., & Lin, C. (2018). Coevolutionary fuzzy attribute order reduction with complete attribute-value space tree. IEEE Transactions on Emerging Topics in Computational Intelligence, https://doi.org/10.1109/tetci.2018.2869919

Since big data sets are structurally complex, high-dimensional, and their attributes exhibit some redundant and irrelevant information, the selection, evaluation, and combination of those large-scale attributes pose huge challenges to traditional met... Read More about Coevolutionary fuzzy attribute order reduction with complete attribute-value space tree.

A Preliminary Study of the Feasibility of Global Evolutionary Feature Selection for Big Datasets under Apache Spark (2018)
Conference Proceeding
Galar, M., Triguero, I., Bustince, H., & Herrera, F. (2018). A Preliminary Study of the Feasibility of Global Evolutionary Feature Selection for Big Datasets under Apache Spark. In 2018 IEEE Congress on Evolutionary Computation (CEC) - Proceedings (1-8). https://doi.org/10.1109/CEC.2018.8477878

Designing efficient learning models capable of dealing with tons of data has become a reality in the era of big data. However, the amount of available data is too much for traditional data mining techniques to be applicable. This issue is even more s... Read More about A Preliminary Study of the Feasibility of Global Evolutionary Feature Selection for Big Datasets under Apache Spark.

A genetic algorithm with composite chromosome for shift assignment of part-time employees (2018)
Conference Proceeding
Xue, N., Landa-Silva, D., Triguero, I., & Figueredo, G. P. (2018). A genetic algorithm with composite chromosome for shift assignment of part-time employees.

Personnel scheduling problems involve multiple tasks, including assigning shifts to workers. The purpose is usually to satisfy objectives and constraints arising from management, labour unions and employee preferences. The shift assignment problem is... Read More about A genetic algorithm with composite chromosome for shift assignment of part-time employees.

A first approach for handling uncertainty in citizen science (2018)
Presentation / Conference
Jiménez, M., Triguero, I., & John, R. (2018, July). A first approach for handling uncertainty in citizen science. Paper presented at IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2018)

Citizen Science is coming to the forefront of scientific research as a valuable method for large-scale processing of data. New technologies in fields such as astronomy or bio-sciences generate tons of data, for which a thorough expert analysis is no... Read More about A first approach for handling uncertainty in citizen science.

Instance reduction for one-class classification (2018)
Journal Article
Krawczyk, B., Triguero, I., García, S., Woźniak, M., & Herrera, F. (in press). Instance reduction for one-class classification. Knowledge and Information Systems, https://doi.org/10.1007/s10115-018-1220-z

Instance reduction techniques are data preprocessing methods originally developed to enhance the nearest neighbor rule for standard classification. They reduce the training data by selecting or generating representative examples of a given problem. T... Read More about Instance reduction for one-class classification.