Statistical analysis with missing data
Statistical analysis with missing data
A Validity Measure for Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
C4.5: programs for machine learning
C4.5: programs for machine learning
Machine learning, neural and statistical classification
Machine learning, neural and statistical classification
Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
ACM Computing Surveys (CSUR)
Fuzzy Modeling for Control
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Feature Selection for Knowledge Discovery and Data Mining
Feature Selection for Knowledge Discovery and Data Mining
Fuzzy Models and Algorithms for Pattern Recognition and Image Processing
Fuzzy Models and Algorithms for Pattern Recognition and Image Processing
Feature Subset Selection Using a Genetic Algorithm
IEEE Intelligent Systems
A Genetic Approach to Fuzzy Clustering with a Validity Measure Fitness Function
IDA '97 Proceedings of the Second International Symposium on Advances in Intelligent Data Analysis, Reasoning about Data
Non-euclidean genetic FCM clustering algorithm
Technologies for constructing intelligent systems
Genetic Algorithms for Feature Selection and Weighting, A Review and Study
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Simulated Annealing Using a Reversible Jump Markov Chain Monte Carlo Algorithm for Fuzzy Clustering
IEEE Transactions on Knowledge and Data Engineering
Toward Integrating Feature Selection Algorithms for Classification and Clustering
IEEE Transactions on Knowledge and Data Engineering
A feature selection technique for classificatory analysis
Pattern Recognition Letters
IEEE Intelligent Systems
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Dimensionality reduction using genetic algorithms
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Information Technology in Biomedicine
Fuzzy c-means clustering of incomplete data
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
On cluster validity for the fuzzy c-means model
IEEE Transactions on Fuzzy Systems
A fuzzy system index to preserve interpretability in deep tuning of fuzzy rule based classifiers
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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Soft computing techniques proved to be successful in many application areas. In this paper we investigate the application in psychopathological field of two well known soft computing techniques, fuzzy logic and genetic algorithms (GAs). The investigation started from a practical need: the creation of a tool for a quick and correct classification of mental retardation level, which is needed to choose the right treatment for rehabilitation and to assure a quality of life that is suitable for the specific patient condition. In order to meet this need we researched an adaptive data mining technique that allows us to build interpretable models for automatic and reliable diagnosis. Our work concerned a genetic fuzzy system (GFS), which integrates a classical GA and the fuzzy C-means (FCM) algorithm. This GFS, called genetic fuzzy C-means (GFCM), is able to select the best subset of features to generate an efficient classifier for diagnostic purposes from a database of examples. Additionally, thanks to an extension of the FCM algorithm, the proposed technique could also handle databases with missing values. The results obtained in a practical application on a real database of patients and comparisons with established techniques showed the efficiency of the integrated algorithm, both in data mining and completion.