Welcome to the website of the IEEE Taskforce on Evolutionary Feature Selection and Construction. We are
passionate to organize events and activities on evolutionary feature selection and construction, to create
opportunities for researchers and industrial practitioners to share ideas, seek collaborations, and make
friends together!
If you are interested in joining this task force or receiving updates from us, please feel free to contact Ruwang Jiao.
News
[Call for paper]: Special Session on Evolutionary Computation for Feature
Selection, Extraction and Dimensionality Reduction, Bach Hoai Nguyen, Ruwang Jiao, Bing Xue, Mengjie Zhang,
IEEE Congress on Evolutionary Computation, 8 June – 12 June
2025, Hangzhou, China.
[IEEE Fellow]: Prof. Bing Xue, our Vice-chair, has been awarded IEEE Fellow,
effective from Jan. 2024.
Scope
In machine learning and data mining, the quality of the input data determines the quality of the output (e.g.
accuracy), known as the GIGO (Garbage In, Garbage Out) principle. For a given problem, the input data of a
learning algorithm is almost always expressed by a number of features (attributes or variables). Therefore, the
quality of the feature space is key for the success of any machine learning and data algorithm.
Many real-world problems involve a large number of features/variables, which leads to the problem known as "the
curse of dimensionality". However, not all features are essential since many of them are redundant or
irrelevant, and the useful features are typically not equally important. This problem can be solved by feature
selection to select a small subset of original features, or feature construction to construct a smaller set of
high-level features using the original low-level features and mathematical or logical operators. Feature
selection and construction are challenging tasks because of the large search space and feature interaction
problems. Due to the powerful search abilities and/or flexible solution encoding/representation schemes, there
has been increasing interest in using evolutionary computation (EC) techniques to solve feature selection and
construction problems. However, the dimensionality and the complexity of the data in real-world problems have grown
fast in recent years, which requires novel effective and efficient approaches to addressing new challenges in
this area.
Mission
Feature selection and construction are important tasks in many areas, such as Data Mining, Machine Learning, Image
Processing and Analysis, Statistics, Operation Research, Biology, Engineering, Finance, and Business. Researchers
from these areas have started investigating EC techniques to solve feature selection and construction problems, but
these researchers attend different events and activities. This task force would be an outstanding platform for them
to share knowledge, exchange ideas, transfer tools, and generate new research lines.
The objectives of this task force are:
To promote the applications of EC techniques to address feature selection and
construction tasks in different areas.
To facilitate collaboration between researchers from related disciplines, such
as Data Mining, Machine Learning, Statistics, Operation Research, Biology, Engineering, Finance, Business,
Image Processing and Analysis, Classification, Clustering, Regression, Medical and Health Care, Networks,
and Security.
To promote discussions and connections between researchers, industrialists, and
practitioners.
Anticipated interests
The theme of this task force is EC for feature selection and construction, covering all different EC paradigms.
Topics of interest include but are not limited to:
Feature ranking/weighting, subset selection, construction, and learning
Novel fitness evaluation criteria in feature selection, construction, and learning
Filter, wrapper, and embedded approaches to feature selection, construction, and learning
Evolutionary deep feature learning
Single objective and multi-objective feature selection and construction
Theoretical analysis on evolutionary feature selection and construction algorithms
Feature extraction/construction in images and video sequences
Feature selection and construction on high-dimensional and large-scale data
EC for feature selection and construction in real-world applications
Feature selection, extraction, and dimensionality reduction in image analysis, pattern recognition,
classification, clustering, regression, and other tasks
Feature selection, extraction, and dimensionality reduction on high-dimensional and large-scale data
Analysis on evolutionary feature selection, extraction, and dimensionality reduction algorithms
Hybridisation of evolutionary computation and neural networks, and fuzzy systems for feature selection and
extraction
Hybridisation of evolutionary computation and machine learning, information theory, statistics, mathematical
modeling, etc., for feature selection and extraction
Real-world applications of evolutionary feature selection and extraction, e.g. images and video
sequences/analysis, face recognition, gene analysis, biomarker detection, medical data classification,
diagnosis, and analysis, hand-written digit recognition, text mining, instrument recognition, power system,
financial and business data analysis, et al.
Past Events and Activities
Tutorial on Evolutionary Computation for Feature Selection and Feature Construction, by Bing Xue, Mengjie Zhang, in The Genetic and Evolutionary Computation
Conference (GECCO2024), July 14 - 18, 2024, Melbourne, Australia.
Tutorial on Evolutionary Feature Reduction for Machine Learning, by Bach Hoai Nguyen, Bing Xue, Mengjie Zhang, in IEEE World Congress on Computational Intelligence (WCCI 2024), 30 June – 5 July 2024, Yokohama, Japan.
Special Session on Evolutionary Computation for Feature Selection, Extraction and Dimensionality Reduction, by Bach Hoai Nguyen, Bing Xue, Yaochu Jin, Mengjie Zhang, in IEEE World Congress on Computational Intelligence (WCCI 2024), 30 June – 5 July 2024, Yokohama, Japan.
Special Session on Evolutionary Multi-objective Machine Learning, by Ruwang Jiao, Bing Xue, Mengjie Zhang, in IEEE World Congress on Computational Intelligence (WCCI 2024), 30 June – 5 July 2024, Yokohama, Japan.
Tutorial on Evolutionary Multi-objective Feature Selection for Machine Learning, by Ruwang Jiao, Bing Xue, Mengjie Zhang, in IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2023), December 5th – 8th 2023, Mexico City, Mexico.
Invited talk on "Evolutionary Multi-objective Feature Selection for Machine Learning", by Ruwang Jiao, in IEEE International Conference on Data Mining and Machine Learning Workshop (IEEE ICDMW 2023), December 1-4, 2023, Shanghai, China.
Special session on Evolutionary Computation for Feature Selection, Extraction and Dimensionality Reduction, in IEEE Congress on Evolutionary Computation (CEC2023).
Tutorial on Evolutionary Computation Success in Medical Diagnosis, in IEEE Congress on Evolutionary Computation (CEC2023).
Tutorial on Evolutionary Feature Reduction for Machine Learning, in IEEE Congress on Evolutionary Computation (CEC2023).
Special Session on Evolutionary Multi-objective Machine Learning, in IEEE Congress on Evolutionary Computation (CEC2023).
Tutorial on Evolutionary Computation for Feature Selection and Feature Construction, in The Genetic and Evolutionary Computation
Conference (GECCO2023).
Special session on Evolutionary Computation for Feature Selection, Extraction and Dimensionality Reduction, in IEEE World Congress on Computational Intelligence (WCCI
2022)/IEEE Congress on Evolutionary Computation (CEC2022).
Tutorial on Evolutionary Feature Reduction for Machine Learning, in IEEE World Congress on
Computational Intelligence (WCCI 2022)/IEEE Congress on Evolutionary Computation (CEC2022).
Tutorial on Evolutionary Computation for Feature Selection and Feature Construction, in The Genetic and Evolutionary Computation
Conference (GECCO2022).
Invited talk on "Evolutionary Computation for Feature Reduction" , by Dr. Bach
Nguyen, in IEEE International Conference on Data Mining and Machine Learning Workshop (IEEE ICDMW 2021).
IEEE Symposium on Computational Intelligence in Feature Analysis, Selection, and Learning in Image and
Pattern Recognition (FASLIP) [Call for Papers], in IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2021).
Tutorial on Evolutionary Computation for Feature Reduction, in IEEE Congress on Evolutionary Computation (CEC2021).
Tutorial on Evolutionary Computation for Feature Selection and Feature Construction, in The Genetic and Evolutionary Computation Conference
(GECCO2021).
Special session on Evolutionary Computation for Feature Selection, Extraction and Dimensionality Reduction, in IEEE Congress on Evolutionary Computation (CEC2021).
IEEE Symposium on Computational Intelligence in Feature Analysis, Selection, and Learning in Image and Pattern Recognition
(FASLIP) [ Call for Papers], in IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2020).
IEEE World Congress on Computational Intelligence (WCCI 2020).
The Genetic and Evolutionary Computation Conference (GECCO 2020).
IEEE Symposium on Computational Intelligence in Feature Analysis, Selection, and Learning in Image and Pattern Recognition
(FASLIP) [ Call for Papers], in IEEE Symposium
Series on Computational Intelligence (IEEE SSCI 2019).
Special session on Evolutionary Computation for Feature Selection, Extraction and Dimensionality Reduction [Call for Papers], in IEEE Congress on Evolutionary Computation (CEC2019).
Special session on Evolutionary Computation for Feature Selection, Extraction and Dimensionality Reduction [Call for Papers], in IEEE Congress on Evolutionary Computation
(WCCI 2018 /CEC2018).
IEEE Symposium on Computational Intelligence in Feature Analysis, Selection, and Learning in Image and Pattern Recognition (FASLIP) [Call for Papers], in IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2018).
IEEE Symposium on Computational Intelligence in Feature Analysis, Selection, and Learning in Image and Pattern Recognition (FASLIP), in IEEE Symposium Series on
Computational Intelligence (IEEE SSCI 2017).
Special session on Evolutionary Computation for Feature Selection, Extraction and Dimensionality Reduction, in The 11th International Conference on Simulated
Evolution and Learning 2017 (SEAL 2017).
Special session on Evolutionary Computation for Feature Selection, Extraction and Dimensionality Reduction, in IEEE Congress on
Evolutionary Computation (CEC2017).
Special Issue on Evolutionary Optimisation, Feature Reduction and Learning, Applied Soft Computing (Journal), Springer, 2017.
Special Session Chair, in The 20th Asia-Pacific
Symposium on Intelligent and Evolutionary Systems (IES2016), Canberra, Australia, November 16-18, 2016.
Special session on Evolutionary Feature Selection and
Construction, in IEEE Congress on Evolutionary
Computation (WCCI 2016 /CEC2016).
Special session on Evolutionary Feature Selection and Construction, in IEEE
Congress on Evolutionary Computation (CEC 2015).
Special session on Evolutionary Feature Reduction, in The Tenth International
Conference on Simulated Evolution And Learning (SEAL 2014).
