Machine Learning
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Information Sciences: an International Journal - Recent advances in genetic fuzzy systems
Feature Generation Using General Constructor Functions
Machine Learning
EuroCOLT '99 Proceedings of the 4th European Conference on Computational Learning Theory
Learning fuzzy classification rules from labeled data
Information Sciences—Informatics and Computer Science: An International Journal - Special issue on recent advances in soft computing
Feature construction for reduction of tabular knowledge-based systems
Information Sciences—Informatics and Computer Science: An International Journal
Constructive induction and genetic algorithms for learning concepts with complex interaction
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Evolutionary Constructive Induction
IEEE Transactions on Knowledge and Data Engineering
Genetic Programming with a Genetic Algorithm for Feature Construction and Selection
Genetic Programming and Evolvable Machines
IEEE Intelligent Systems
Statistical Comparisons of Classifiers over Multiple Data Sets
The Journal of Machine Learning Research
Feature Selection via Coalitional Game Theory
Neural Computation
Feature selection for multi-label naive Bayes classification
Information Sciences: an International Journal
Kernels for Periodic Time Series Arising in Astronomy
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II
Unified video annotation via multigraph learning
IEEE Transactions on Circuits and Systems for Video Technology
Feature generation for text categorization using world knowledge
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Information Sciences: an International Journal
Applying electromagnetism-like mechanism for feature selection
Information Sciences: an International Journal
Sequential covering rule induction algorithm for variable consistency rough set approaches
Information Sciences: an International Journal
A feature construction approach for genetic iterative rule learning algorithm
Journal of Computer and System Sciences
Inferring ECA-based rules for ambient intelligence using evolutionary feature extraction
Journal of Ambient Intelligence and Smart Environments
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This paper presents a new feature discovery approach called FEADIS that strengthens learning algorithms with discovered features. The discovered features are formed by various mathematical functions including ceil, mod, sin, and similar. These features are constructed in an iterative manner to improve gradually its learning performance. We demonstrate FEADIS capabilities by testing different types of datasets including periodical datasets. From the results, we conclude that FEADIS increases the performance of learning algorithms in a wide range of datasets for nominal or numeric target feature. Furthermore, most of the well known classifiers without FEADIS strengthening have severe difficulty in handling datasets that have periodical functional relations between input features and target feature - a difficulty circumvented by their potential use of FEADIS.