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Go to Feature Extraction

Beceiro B, González-Domínguez J, Morán-Fernández L, Bolón-Canedo V and Touriño J (2024). CUDA acceleration of MI-based feature selection methods, Journal of Parallel and Distributed Computing , 190 :C , Online publication date: 1-Aug-2024 .

Alfaro J, Aledo J and Gámez J (2023). Multi-dimensional Bayesian network classifiers for partial label ranking, International Journal of Approximate Reasoning , 160 :C , Online publication date: 1-Sep-2023 .

Liu Z, Xu W, Zhang W and Jiang Q (2023). An emotion-based personalized music recommendation framework for emotion improvement, Information Processing and Management: an International Journal , 60 :3 , Online publication date: 1-May-2023 .

Li Y, Hu L and Gao W (2023). Multi-label feature selection via robust flexible sparse regularization, Pattern Recognition , 134 :C , Online publication date: 1-Feb-2023 .

Ye X, Liu D and Li T (2023). Multi-granularity sequential three-way recommendation based on collaborative deep learning, International Journal of Approximate Reasoning , 152 :C , (434-455), Online publication date: 1-Jan-2023 .

Arjomandi Rad M, Salomonsson K, Cenanovic M, Balague H, Raudberget D and Stolt R (2022). Correlation-based feature extraction from computer-aided design, case study on curtain airbags design, Computers in Industry , 138 :C , Online publication date: 1-Jun-2022 .

Sharma M, Darji J, Thakrar M and Acharya U (2022). Automated identification of sleep disorders using wavelet-based features extracted from electrooculogram and electromyogram signals, Computers in Biology and Medicine , 143 :C , Online publication date: 1-Apr-2022 .

Na G and Chang H (2021). Unsupervised Subspace Extraction via Deep Kernelized Clustering, ACM Transactions on Knowledge Discovery from Data , 16 :1 , (1-15), Online publication date: 28-Feb-2022 .

Arora T, Balasubramanian V and Mai S Prioritization of Clinical Alarms using Semantic Features of Vital Signs in Remote Patient Monitoring Australasian Computer Science Week 2022, (242-245)

Petković M, Škrlj B, Kocev D and Simidjievski N (2021). Fuzzy Jaccard Index, Applied Soft Computing , 113 :PA , Online publication date: 1-Dec-2021 .

Li F, Xu L, You T and Lu A (2021). Measurement of potentially toxic elements in the soil through NIR, MIR, and XRF spectral data fusion, Computers and Electronics in Agriculture , 187 :C , Online publication date: 1-Aug-2021 .

Bharti R, Khamparia A, Shabaz M, Dhiman G, Pande S, Singh P and Abd El-Latif A (2021). Prediction of Heart Disease Using a Combination of Machine Learning and Deep Learning, Computational Intelligence and Neuroscience , 2021 , Online publication date: 1-Jan-2021 .

Xie H and Qin Z (2020). A Lite Distributed Semantic Communication System for Internet of Things, IEEE Journal on Selected Areas in Communications , 39 :1 , (142-153), Online publication date: 1-Jan-2021 .

Lee S, Lim J, Cho J, Oh S, Whangbo T and Choi C A Classification method of Fake News based on Ensemble Learning Proceedings of the 2020 ACM International Conference on Intelligent Computing and its Emerging Applications, (1-4)

do Rêgo L, da Silva T, Magalhães R, de Macêdo J and Silva W Exploiting points of interest for predictive policing Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Advances in Resilient and Intelligent Cities, (20-28)

Mishra P, Verma I and Gupta S (2020). KVMInspector, Journal of Information Security and Applications , 51 :C , Online publication date: 1-Apr-2020 .

Umar M, Zhanfang C and Liu Y Network Intrusion Detection Using Wrapper-based Decision Tree for Feature Selection Proceedings of the 2020 International Conference on Internet Computing for Science and Engineering, (5-13)

Krishnamurthy P, Karri R and Khorrami F (2019). Anomaly Detection in Real-Time Multi-Threaded Processes Using Hardware Performance Counters, IEEE Transactions on Information Forensics and Security , 15 , (666-680), Online publication date: 1-Jan-2020 .

Shah M, Tu M, Berisha V, Chakrabarti C and Spanias A (2019). Articulation constrained learning with application to speech emotion recognition, EURASIP Journal on Audio, Speech, and Music Processing , 2019 :1 , (1-17), Online publication date: 1-Dec-2019 .

Russell M, Zou J, Fang G and Cai W (2019). Feature-Based Image Patch Classification for Moving Shadow Detection, IEEE Transactions on Circuits and Systems for Video Technology , 29 :9 , (2652-2666), Online publication date: 1-Sep-2019 .

Remeseiro B and Bolon-Canedo V (2019). A review of feature selection methods in medical applications, Computers in Biology and Medicine , 112 :C , Online publication date: 1-Sep-2019 .

Ayodele M Application of estimation of distribution algorithm for feature selection Proceedings of the Genetic and Evolutionary Computation Conference Companion, (43-44)

Barceló P, Baumgartner A, Dalmau V and Kimelfeld B Regularizing Conjunctive Features for Classification Proceedings of the 38th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems, (2-16)

Beuzen T and Simmons J (2019). A variable selection package driving Netica with Python, Environmental Modelling & Software , 115 :C , (1-5), Online publication date: 1-May-2019 .

Zheng W, Yan H and Yang J (2019). Robust unsupervised feature selection by nonnegative sparse subspace learning, Neurocomputing , 334 :C , (156-171), Online publication date: 21-Mar-2019 .

Boullé M, Charnay C and Lachiche N (2019). A scalable robust and automatic propositionalization approach for Bayesian classification of large mixed numerical and categorical data, Machine Language , 108 :2 , (229-266), Online publication date: 1-Feb-2019 .

Pereira L, Papa J, Coelho A, Lima C, Pereira D and Albuquerque V (2019). Automatic identification of epileptic EEG signals through binary magnetic optimization algorithms, Neural Computing and Applications , 31 :2 , (1317-1329), Online publication date: 1-Feb-2019 .

Coelho F, Castro C, Braga A and Verleysen M (2019). Semi-supervised relevance index for feature selection, Neural Computing and Applications , 31 :2 , (989-997), Online publication date: 1-Feb-2019 .

Li J, Cheng K, Wang S, Morstatter F, Trevino R, Tang J and Liu H (2017). Feature Selection, ACM Computing Surveys , 50 :6 , (1-45), Online publication date: 30-Nov-2018 .

Kimelfeld B and Ré C (2018). A Relational Framework for Classifier Engineering, ACM Transactions on Database Systems , 43 :3 , (1-36), Online publication date: 26-Nov-2018 .

Kuralenok I, Starikova N, Khvorov A and Serdyuk J Construction of Efficient V-Gram Dictionary for Sequential Data Analysis Proceedings of the 27th ACM International Conference on Information and Knowledge Management, (1343-1352)

Allerhand L, Youngmann B, Yom-Tov E and Arkadir D Detecting Parkinson's Disease from Interactions with a Search Engine Proceedings of the 27th ACM International Conference on Information and Knowledge Management, (1539-1542)

Al-Ani A and Mesbah M (2018). EEG rhythm/channel selection for fuzzy rule-based alertness state characterization, Neural Computing and Applications , 30 :7 , (2257-2267), Online publication date: 1-Oct-2018 .

Kimelfeld B and Ré C (2018). A Relational Framework for Classifier Engineering, ACM SIGMOD Record , 47 :1 , (6-13), Online publication date: 10-Sep-2018 .

Banaee H, Schaffernicht E and Loutfi A (2019). Data-driven conceptual spaces, Journal of Artificial Intelligence Research , 63 :1 , (691-742), Online publication date: 1-Sep-2018 .

Bolón-Canedo V, Rego-Fernández D, Peteiro-Barral D, Alonso-Betanzos A, Guijarro-Berdiñas B and Sánchez-Maroño N (2018). On the scalability of feature selection methods on high-dimensional data, Knowledge and Information Systems , 56 :2 , (395-442), Online publication date: 1-Aug-2018 .

Lpez J, Maldonado S and Carrasco M (2018). Double regularization methods for robust feature selection and SVM classification via DC programming, Information Sciences: an International Journal , 429 :C , (377-389), Online publication date: 1-Mar-2018 .

Abidine B, Fergani L, Fergani B and Oussalah M (2018). The joint use of sequence features combination and modified weighted SVM for improving daily activity recognition, Pattern Analysis & Applications , 21 :1 , (119-138), Online publication date: 1-Feb-2018 .

Oliveira R, Papa J, Pereira A and Tavares J (2018). Computational methods for pigmented skin lesion classification in images, Neural Computing and Applications , 29 :3 , (613-636), Online publication date: 1-Feb-2018 .

Ouyed O and Allili M (2018). Feature weighting for multinomial kernel logistic regression and application to action recognition, Neurocomputing , 275 :C , (1752-1768), Online publication date: 31-Jan-2018 .

Qi M, Wang T, Liu F, Zhang B, Wang J and Yi Y (2018). Unsupervised feature selection by regularized matrix factorization, Neurocomputing , 273 :C , (593-610), Online publication date: 17-Jan-2018 .

Hancer E, Xue B and Zhang M (2018). Differential evolution for filter feature selection based on information theory and feature ranking, Knowledge-Based Systems , 140 :C , (103-119), Online publication date: 15-Jan-2018 .

Pratiwi A, Adiwijaya and Zunino R (2018). On the Feature Selection and Classification Based on Information Gain for Document Sentiment Analysis, Applied Computational Intelligence and Soft Computing , 2018 , Online publication date: 1-Jan-2018 .

Aladeemy M, Tutun S and Khasawneh M (2017). A new hybrid approach for feature selection and support vector machine model selection based on self-adaptive cohort intelligence, Expert Systems with Applications: An International Journal , 88 :C , (118-131), Online publication date: 1-Dec-2017 .

Seijo-Pardo B, Bolón-Canedo V and Alonso-Betanzos A (2017). Testing Different Ensemble Configurations for Feature Selection, Neural Processing Letters , 46 :3 , (857-880), Online publication date: 1-Dec-2017 .

Li Y, Li T and Liu H (2017). Recent advances in feature selection and its applications, Knowledge and Information Systems , 53 :3 , (551-577), Online publication date: 1-Dec-2017 .

Gaudioso M, Gorgone E, Labb M and Rodrguez-Cha A (2017). Lagrangian relaxation for SVM feature selection, Computers and Operations Research , 87 :C , (137-145), Online publication date: 1-Nov-2017 .

Shah V, Kumar A and Zhu X (2017). Are key-foreign key joins safe to avoid when learning high-capacity classifiers?, Proceedings of the VLDB Endowment , 11 :3 , (366-379), Online publication date: 1-Nov-2017 .

Pintas J, Correia L and Bicharra Garcia A (2017). Crowd-based Feature Selection for Document Retrieval in Highly Demanding Decision-making Scenarios, Procedia Computer Science , 112 :C , (822-832), Online publication date: 1-Sep-2017 .

Viegas R, Salgado C, Curto S, Carvalho J, Vieira S and Finkelstein S (2017). Daily prediction of ICU readmissions using feature engineering and ensemble fuzzy modeling, Expert Systems with Applications: An International Journal , 79 :C , (244-253), Online publication date: 15-Aug-2017 .

Goswami S, Das A, Chakrabarti A and Chakraborty B (2017). A feature cluster taxonomy based feature selection technique, Expert Systems with Applications: An International Journal , 79 :C , (76-89), Online publication date: 15-Aug-2017 .

Chang C, Chang C, Kathiravan S, Lin C and Chen S (2017). DAG-SVM based infant cry classification system using sequential forward floating feature selection, Multidimensional Systems and Signal Processing , 28 :3 , (961-976), Online publication date: 1-Jul-2017 .

Du S, Ma Y, Li S and Ma Y (2017). Robust unsupervised feature selection via matrix factorization, Neurocomputing , 241 :C , (115-127), Online publication date: 7-Jun-2017 .

(2017). A new feature selection method based on a validity index of feature subset, Pattern Recognition Letters , 92 :C , (1-8), Online publication date: 1-Jun-2017 .

Maldonado S, Montoya R and López J (2017). Embedded heterogeneous feature selection for conjoint analysis, Applied Intelligence , 46 :4 , (775-787), Online publication date: 1-Jun-2017 .

Chen L, Koutris P and Kumar A Model-based Pricing Proceedings of the 1st Workshop on Data Management for End-to-End Machine Learning, (1-4)

Kumar A, Boehm M and Yang J Data Management in Machine Learning Proceedings of the 2017 ACM International Conference on Management of Data, (1717-1722)

Kimelfeld B and Ré C A Relational Framework for Classifier Engineering Proceedings of the 36th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems, (5-20)

Lpez J and Maldonado S (2017). Group-penalized feature selection and robust twin SVM classification via second-order cone programming, Neurocomputing , 235 :C , (112-121), Online publication date: 26-Apr-2017 .

Cao P, Liu X, Zhang J, Zhao D, Huang M and Zaiane O (2017). 2,1 norm regularized multi-kernel based joint nonlinear feature selection and over-sampling for imbalanced data classification, Neurocomputing , 234 :C , (38-57), Online publication date: 19-Apr-2017 .

Cano G, Garcia-Rodriguez J, Garcia-Garcia A, Perez-Sanchez H, Benediktsson J, Thapa A and Barr A (2017). Automatic selection of molecular descriptors using random forest, Expert Systems with Applications: An International Journal , 72 :C , (151-159), Online publication date: 15-Apr-2017 .

Wang J, Wei J, Yang Z and Wang S (2017). Feature Selection by Maximizing Independent Classification Information, IEEE Transactions on Knowledge and Data Engineering , 29 :4 , (828-841), Online publication date: 1-Apr-2017 .

Liu C, Wang W, Konan M, Wang S, Huang L, Tang Y and Zhang X (2017). A new validity index of feature subset for evaluating the dimensionality reduction algorithms, Knowledge-Based Systems , 121 :C , (83-98), Online publication date: 1-Apr-2017 .

Cano A, Ventura S and Cios K (2017). Multi-objective genetic programming for feature extraction and data visualization, Soft Computing - A Fusion of Foundations, Methodologies and Applications , 21 :8 , (2069-2089), Online publication date: 1-Apr-2017 .

Mera D, Bolon-Canedo V, Cotos J and Alonso-Betanzos A (2017). On the use of feature selection to improve the detection of sea oil spills in SAR images, Computers & Geosciences , 100 :C , (166-178), Online publication date: 1-Mar-2017 .

Barbu A, She Y, Ding L and Gramajo G (2017). Feature Selection with Annealing for Computer Vision and Big Data Learning, IEEE Transactions on Pattern Analysis and Machine Intelligence , 39 :2 , (272-286), Online publication date: 1-Feb-2017 .

Escalante H, Guyon I, Athitsos V, Jangyodsuk P and Wan J (2017). Principal motion components for one-shot gesture recognition, Pattern Analysis & Applications , 20 :1 , (167-182), Online publication date: 1-Feb-2017 .

Blasco J, Chen T, Tapiador J and Peris-Lopez P (2016). A Survey of Wearable Biometric Recognition Systems, ACM Computing Surveys , 49 :3 , (1-35), Online publication date: 13-Dec-2016 .

Torrecilla J and Suárez A Feature selection in functional data classification with recursive maxima hunting Proceedings of the 30th International Conference on Neural Information Processing Systems, (4842-4850)

Pehlivanl A, Akgil B and Glay G (2016). Indicator selection with committee decision of filter methods for stock market price trend in ISE, Applied Soft Computing , 49 :C , (792-800), Online publication date: 1-Dec-2016 .

Benabdeslem K, Elghazel H and Hindawi M (2016). Ensemble constrained Laplacian score for efficient and robust semi-supervised feature selection, Knowledge and Information Systems , 49 :3 , (1161-1185), Online publication date: 1-Dec-2016 .

Liu M and Zhang D (2016). Feature selection with effective distance, Neurocomputing , 215 :C , (100-109), Online publication date: 26-Nov-2016 .

Yu J, Zhang X and Li F (2016). Spatial steganalysis using redistributed residuals and diverse ensemble classifier, Multimedia Tools and Applications , 75 :21 , (13613-13625), Online publication date: 1-Nov-2016 .

Erfani S, Rajasegarar S, Karunasekera S and Leckie C (2016). High-dimensional and large-scale anomaly detection using a linear one-class SVM with deep learning, Pattern Recognition , 58 :C , (121-134), Online publication date: 1-Oct-2016 .

Tapia J, Perez C and Bowyer K (2016). Gender Classification From the Same Iris Code Used for Recognition, IEEE Transactions on Information Forensics and Security , 11 :8 , (1760-1770), Online publication date: 1-Aug-2016 .

Vallejo M, Cosgrove J, Alty J, Jamieson S, Smith S, Corne D and Lones M A Multi-Objective Approach to Predicting Motor and Cognitive Deficit in Parkinson's Disease Patients Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion, (1369-1376)

Kumar A, Naughton J, Patel J and Zhu X To Join or Not to Join? Proceedings of the 2016 International Conference on Management of Data, (19-34)

Kumar A, McCann R, Naughton J and Patel J (2016). Model Selection Management Systems, ACM SIGMOD Record , 44 :4 , (17-22), Online publication date: 9-May-2016 .

Zhang C, Kumar A and Ré C (2016). Materialization Optimizations for Feature Selection Workloads, ACM Transactions on Database Systems , 41 :1 , (1-32), Online publication date: 7-Apr-2016 .

Zou P, Wang J, Chen S and Chen H (2016). Margin distribution explanation on metric learning for nearest neighbor classification, Neurocomputing , 177 :C , (168-178), Online publication date: 12-Feb-2016 .

Golay J and Kanevski M (2015). A new estimator of intrinsic dimension based on the multipoint Morisita index, Pattern Recognition , 48 :12 , (4070-4081), Online publication date: 1-Dec-2015 .

Torrano-Gimenez C, Nguyen H, Alvarez G and Franke K (2015). Combining expert knowledge with automatic feature extraction for reliable web attack detection, Security and Communication Networks , 8 :16 , (2750-2767), Online publication date: 10-Nov-2015 .

Maldonado S, Flores Á, Verbraken T, Baesens B and Weber R (2015). Profit-based feature selection using support vector machines - General framework and an application for customer retention, Applied Soft Computing , 35 :C , (740-748), Online publication date: 1-Oct-2015 .

Rehman A, Javed K, Babri H and Saeed M (2015). Relative discrimination criterion - A novel feature ranking method for text data, Expert Systems with Applications: An International Journal , 42 :7 , (3670-3681), Online publication date: 1-May-2015 .

Schleif F (2015). Generic probabilistic prototype based classification of vectorial and proximity data, Neurocomputing , 154 :C , (208-216), Online publication date: 22-Apr-2015 .

(2015). Unsupervised feature selection via maximum projection and minimum redundancy, Knowledge-Based Systems , 75 :C , (19-29), Online publication date: 1-Feb-2015 .

Wang S, Pedrycz W, Zhu Q and Zhu W (2015). Subspace learning for unsupervised feature selection via matrix factorization, Pattern Recognition , 48 :1 , (10-19), Online publication date: 1-Jan-2015 .

Galelli S, Humphrey G, Maier H, Castelletti A, Dandy G and Gibbs M (2014). An evaluation framework for input variable selection algorithms for environmental data-driven models, Environmental Modelling & Software , 62 :C , (33-51), Online publication date: 1-Dec-2014 .

Newell A, Potharaju R, Xiang L and Nita-Rotaru C On the Practicality of Integrity Attacks on Document-Level Sentiment Analysis Proceedings of the 2014 Workshop on Artificial Intelligent and Security Workshop, (83-93)

Zuo Z, Luo Y, Tao D and Xu C Multi-view Multi-task Feature Extraction for Web Image Classification Proceedings of the 22nd ACM international conference on Multimedia, (1137-1140)

Ditzler G and Rosen G Feature subset selection for inferring relative importance of taxonomy Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, (673-679)

Sechidis K, Nikolaou N and Brown G Information Theoretic Feature Selection in Multi-label Data through Composite Likelihood Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition - Volume 8621, (143-152)

Garcia-Limon M, Escalante H, Morales E and Morales-Reyes A Simultaneous generation of prototypes and features through genetic programming Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation, (517-524)

Xu H, Zhou Y and Lyu M Towards continuous and passive authentication via touch biometrics Proceedings of the Tenth USENIX Conference on Usable Privacy and Security, (187-198)

Zhang C, Kumar A and Ré C Materialization optimizations for feature selection workloads Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data, (265-276)

Chai J, Chen H, Huang L and Shang F (2014). Maximum margin multiple-instance feature weighting, Pattern Recognition , 47 :6 , (2091-2103), Online publication date: 1-Jun-2014 .

Liu B, Xiao Y, Yu P, Hao Z and Cao L (2014). An efficient orientation distance---based discriminative feature extraction method for multi-classification, Knowledge and Information Systems , 39 :2 , (409-433), Online publication date: 1-May-2014 .

Tanathong S and Banharnsakun A Multiple Object Tracking Based on a Hierarchical Clustering of Features Approach Proceedings, Part I, of the 6th Asian Conference on Intelligent Information and Database Systems - Volume 8397, (522-529)

Rodrigues D, Pereira L, Nakamura R, Costa K, Yang X, Souza A and Papa J (2014). A wrapper approach for feature selection based on Bat Algorithm and Optimum-Path Forest, Expert Systems with Applications: An International Journal , 41 :5 , (2250-2258), Online publication date: 1-Apr-2014 .

Frénay B, Doquire G and Verleysen M (2014). Estimating mutual information for feature selection in the presence of label noise, Computational Statistics & Data Analysis , 71 :C , (832-848), Online publication date: 1-Mar-2014 .

Ferreira A and Figueiredo M (2014). Incremental filter and wrapper approaches for feature discretization, Neurocomputing , 123 , (60-74), Online publication date: 1-Jan-2014 .

Min F, Hu Q and Zhu W (2014). Feature selection with test cost constraint, International Journal of Approximate Reasoning , 55 :1 , (167-179), Online publication date: 1-Jan-2014 .

Rodriguez-Lujan I, Bailador G, Sanchez-Avila C, Herrero A and Vidal-De-Miguel G (2013). Analysis of pattern recognition and dimensionality reduction techniques for odor biometrics, Knowledge-Based Systems , 52 , (279-289), Online publication date: 1-Nov-2013 .

Hoai Minh L and Minh Thuy T DC Programming and DCA for Solving Minimum Sum-of-Squares Clustering Using Weighted Dissimilarity Measures Transactions on Computational Intelligence XIII - Volume 8342, (113-131)

Guan J, Han F and Yang S A new gene selection method for microarray data based on PSO and informativeness metric Proceedings of the 9th international conference on Intelligent Computing Theories and Technology, (145-154)

Bolón-Canedo V, Sánchez-Maroño N and Alonso-Betanzos A (2013). A review of feature selection methods on synthetic data, Knowledge and Information Systems , 34 :3 , (483-519), Online publication date: 1-Mar-2013 .

Lindawati , Yuan Z, Lau H and Zhu F Automated Parameter Tuning Framework for Heterogeneous and Large Instances Revised Selected Papers of the 7th International Conference on Learning and Intelligent Optimization - Volume 7997, (423-437)

Sengstock C and Gertz M Latent geographic feature extraction from social media Proceedings of the 20th International Conference on Advances in Geographic Information Systems, (149-158)

Gibert J, Valveny E and Bunke H (2012). Feature selection on node statistics based embedding of graphs, Pattern Recognition Letters , 33 :15 , (1980-1990), Online publication date: 1-Nov-2012 .

Ferreira A and Figueiredo M (2012). Efficient feature selection filters for high-dimensional data, Pattern Recognition Letters , 33 :13 , (1794-1804), Online publication date: 1-Oct-2012 .

Blachnik M, Duch W and Maszczyk T Feature ranking methods used for selection of prototypes Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part II, (296-304)

Diong M, Bas P, Pelle C and Sawaya W Document authentication using 2d codes Proceedings of the 13th IFIP TC 6/TC 11 international conference on Communications and Multimedia Security, (39-54)

Ferreira A and Figueiredo M (2012). An unsupervised approach to feature discretization and selection, Pattern Recognition , 45 :9 , (3048-3060), Online publication date: 1-Sep-2012 .

Almeida S, Coelho F, Guimarães F and Braga A A general approach for adaptive kernels in semi-supervised clustering Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning, (508-515)

Mao Y, Chen W, Chen Y, Lu C, Kollef M and Bailey T An integrated data mining approach to real-time clinical monitoring and deterioration warning Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, (1140-1148)

Ozcift A (2012). Enhanced Cancer Recognition System Based on Random Forests Feature Elimination Algorithm, Journal of Medical Systems , 36 :4 , (2577-2585), Online publication date: 1-Aug-2012 .

Nguyen H and Franke K A general lp-norm support vector machine via mixed 0-1 programming Proceedings of the 8th international conference on Machine Learning and Data Mining in Pattern Recognition, (40-49)

Cazenille L, Bredeche N, Hamann H and Stradner J Impact of neuron models and network structure on evolving modular robot neural network controllers Proceedings of the 14th annual conference on Genetic and evolutionary computation, (89-96)

Zhu Z, Shen L, Sun Y, He S and Ji Z Memetic three-dimensional gabor feature extraction for hyperspectral imagery classification Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part I, (479-488)

Paulheim H and Fümkranz J Unsupervised generation of data mining features from linked open data Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics, (1-12)

Paulheim H Generating possible interpretations for statistics from linked open data Proceedings of the 9th international conference on The Semantic Web: research and applications, (560-574)

Zoppis I, Gianazza E, Borsani M, Chinello C, Mainini V, Galbusera C, Ferrarese C, Galimberti G, Sorbi S, Borroni B, Magni F, Antoniotti M and Mauri G (2012). Mutual Information Optimization for Mass Spectra Data Alignment, IEEE/ACM Transactions on Computational Biology and Bioinformatics , 9 :3 , (934-939), Online publication date: 1-May-2012 .

Marini S and Conversi A Understanding zooplankton long term variability through genetic programming Proceedings of the 10th European conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, (50-61)

Ozcift A and Gulten A (2012). A Robust Multi-Class Feature Selection Strategy Based on Rotation Forest Ensemble Algorithm for Diagnosis of Erythemato-Squamous Diseases, Journal of Medical Systems , 36 :2 , (941-949), Online publication date: 1-Apr-2012 .

Tam T, Ferreira A and Lourenço A Automatic foldering of email messages Proceedings of the 34th European conference on Advances in Information Retrieval, (232-243)

Derrac J, Cornelis C, García S and Herrera F (2012). Enhancing evolutionary instance selection algorithms by means of fuzzy rough set based feature selection, Information Sciences: an International Journal , 186 :1 , (73-92), Online publication date: 1-Mar-2012 .

Li J, Burke E and Qu R (2012). A pattern recognition based intelligent search method and two assignment problem case studies, Applied Intelligence , 36 :2 , (442-453), Online publication date: 1-Mar-2012 .

Vieira S, Sousa J and Kaymak U (2012). Fuzzy criteria for feature selection, Fuzzy Sets and Systems , 189 :1 , (1-18), Online publication date: 1-Feb-2012 .

El-Monsef M, Abu-Donia H and Marei E Multi-valued approach to near set theory Transactions on Rough Sets XV, (26-40)

BolóN-Canedo V, SáNchez-MaroñO N and Alonso-Betanzos A (2012). An ensemble of filters and classifiers for microarray data classification, Pattern Recognition , 45 :1 , (531-539), Online publication date: 1-Jan-2012 .

Gudmundsson S, Runarsson T and Sigurdsson S (2012). Test-retest reliability and feature selection in physiological time series classification, Computer Methods and Programs in Biomedicine , 105 :1 , (50-60), Online publication date: 1-Jan-2012 .

Maldonado S and Weber R Embedded feature selection for support vector machines Proceedings of the 16th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, (304-311)

Li R, Liu K, He Y and Zhao J Does feature matter Proceedings of the 6th International Conference on Body Area Networks, (85-91)

Bolón-Canedo V, Peteiro-Barral D, Alonso-Betanzos A, Guijarro-Berdiñas B and Sánchez-Maroño N Scalability analysis of ANN training algorithms with feature selection Proceedings of the 14th international conference on Advances in artificial intelligence: spanish association for artificial intelligence, (84-93)

Zakharov R and Dupont P Ensemble logistic regression for feature selection Proceedings of the 6th IAPR international conference on Pattern recognition in bioinformatics, (133-144)

Janusz A and Stawicki S Applications of approximate reducts to the feature selection problem Proceedings of the 6th international conference on Rough sets and knowledge technology, (45-50)

Zhang Z and Hancock E Mutual information criteria for feature selection Proceedings of the First international conference on Similarity-based pattern recognition, (235-249)

Hou Y and Zheng X SVM based MLP neural network algorithm and application in intrusion detection Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part III, (340-345)

Guzmán-Martínez R and Alaiz-Rodríguez R Feature selection stability assessment based on the Jensen-Shannon divergence Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part I, (597-612)

Guzmán-Martínez R and Alaiz-Rodríguez R Feature selection stability assessment based on the Jensen-Shannon divergence Proceedings of the 2011th European Conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I, (597-612)

Aggarwal V, George A, Yoon C, Yalamanchili K and Lam H (2011). SHMEM+, ACM Transactions on Reconfigurable Technology and Systems , 4 :3 , (1-24), Online publication date: 1-Aug-2011 .

Vatolkin I, Preuß M and Rudolph G Multi-objective feature selection in music genre and style recognition tasks Proceedings of the 13th annual conference on Genetic and evolutionary computation, (411-418)

Grbczewski K and Jankowski N (2011). Saving time and memory in computational intelligence system with machine unification and task spooling, Knowledge-Based Systems , 24 :5 , (570-588), Online publication date: 1-Jul-2011 .

Popescu F and Renz D Compression and learning in linear regression Proceedings of the 19th international conference on Foundations of intelligent systems, (270-279)

Csirik J, Bertholet P and Bunke H Sequential classifier combination for pattern recognition in wireless sensor networks Proceedings of the 10th international conference on Multiple classifier systems, (187-196)

Nguyen H, Torrano-Gimenez C, Alvarez G, Petrović S and Franke K Application of the generic feature selection measure in detection of web attacks Proceedings of the 4th international conference on Computational intelligence in security for information systems, (25-32)

Ferreira A and Figueiredo M Unsupervised joint feature discretization and selection Proceedings of the 5th Iberian conference on Pattern recognition and image analysis, (200-207)

Icke I and Rosenberg A Multi-objective genetic programming for visual analytics Proceedings of the 14th European conference on Genetic programming, (322-334)

Csirik J, Bertholet P and Bunke H Pattern recognition in wireless sensor networks in presence of sensor failures Proceedings of the 12th WSEAS international conference on Neural networks, fuzzy systems, evolutionary computing & automation, (104-109)

Nguyen H, Franke K and Petrovic S (2011). Improving Effectiveness of Intrusion Detection by Correlation Feature Selection, International Journal of Mobile Computing and Multimedia Communications , 3 :1 , (21-34), Online publication date: 1-Jan-2011 .

Aggarwal V, Yoon C, George A, Lam H and Stitt G Performance modeling for multilevel communication in SHMEM+ Proceedings of the Fourth Conference on Partitioned Global Address Space Programming Model, (1-10)

Maszczyk T and Duch W Almost random projection machine with margin maximization and kernel features Proceedings of the 20th international conference on Artificial neural networks: Part II, (40-48)

Nguyen H, Petrović S and Franke K A comparison of feature-selection methods for intrusion detection Proceedings of the 5th international conference on Mathematical methods, models and architectures for computer network security, (242-255)

Esseghir M, Goncalves G and Slimani Y Adaptive particle swarm optimizer for feature selection Proceedings of the 11th international conference on Intelligent data engineering and automated learning, (226-233)

Yang J and Ong C Feature selection for support vector regression using probabilistic prediction Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining, (343-352)

Khosla A, Cao Y, Lin C, Chiu H, Hu J and Lee H An integrated machine learning approach to stroke prediction Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining, (183-192)

Féraud R, Boullé M, Clérot F, Fessant F and Lemaire V The orange customer analysis platform Proceedings of the 10th industrial conference on Advances in data mining: applications and theoretical aspects, (584-594)

Lichodzijewski P and Heywood M Symbiosis, complexification and simplicity under GP Proceedings of the 12th annual conference on Genetic and evolutionary computation, (853-860)

Pevný T, Filler T and Bas P Using high-dimensional image models to perform highly undetectable steganography Proceedings of the 12th international conference on Information hiding, (161-177)

Schön T, Tsymbal A and Huber M Gene-pair representation and incorporation of GO-based semantic similarity into classification of gene expression data Proceedings of the 7th international conference on Rough sets and current trends in computing, (217-226)

Drozdz K and Kwasnicka H Feature set reduction by evolutionary selection and construction Proceedings of the 4th KES international conference on Agent and multi-agent systems: technologies and applications, Part II, (140-149)

Esseghir M, Goncalves G and Slimani Y Memetic feature selection Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part I, (351-358)

Bontempi G and Meyer P Causal filter selection in microarray data Proceedings of the 27th International Conference on International Conference on Machine Learning, (95-102)

Kachel A, Biesiada J, Blachnik M and Duch W Infosel++ Proceedings of the 10th international conference on Artificial intelligence and soft computing: Part I, (388-396)

Grąbczewski K and Jankowski N Task management in advanced computational intelligence system Proceedings of the 10th international conference on Artificial intelligence and soft computing: Part I, (331-338)

Blachnik M, Bukowiec A, Kordos M and Biesiada J Information theory vs. correlation based feature ranking methods in application to metallurgical problem solving Proceedings of the 10th international conference on Artificial intelligence and soft computing: Part I, (289-298)

Dudek G Tournament searching method to feature selection problem Proceedings of the 10th international conference on Artifical intelligence and soft computing: Part II, (437-444)

Ludwig O and Nunes U (2010). Novel maximum-margin training algorithms for supervised neural networks, IEEE Transactions on Neural Networks , 21 :6 , (972-984), Online publication date: 1-Jun-2010 .

Martínez Sotoca J and Pla F (2010). Supervised feature selection by clustering using conditional mutual information-based distances, Pattern Recognition , 43 :6 , (2068-2081), Online publication date: 1-Jun-2010 .

Marini S, Patané G, Spagnuolo M and Falcidieno B Feature selection for enhanced spectral shape comparison Proceedings of the 3rd Eurographics conference on 3D Object Retrieval, (31-38)

Aliferis C, Statnikov A, Tsamardinos I, Mani S and Koutsoukos X (2010). Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part II: Analysis and Extensions, The Journal of Machine Learning Research , 11 , (235-284), Online publication date: 1-Mar-2010 .

Aliferis C, Statnikov A, Tsamardinos I, Mani S and Koutsoukos X (2010). Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part I: Algorithms and Empirical Evaluation, The Journal of Machine Learning Research , 11 , (171-234), Online publication date: 1-Mar-2010 .

Guyon I, Saffari A, Dror G and Cawley G (2010). Model Selection: Beyond the Bayesian/Frequentist Divide, The Journal of Machine Learning Research , 11 , (61-87), Online publication date: 1-Mar-2010 .

Flores M, Armingol J and de la Escalera A (2010). Driver drowsiness warning system using visual information for both diurnal and nocturnal illumination conditions, EURASIP Journal on Advances in Signal Processing , 2010 , (1-19), Online publication date: 1-Mar-2010 .

Zhuo C, Chang Y, Sylvester D and Blaauw D Design time body bias selection for parametric yield improvement Proceedings of the 2010 Asia and South Pacific Design Automation Conference, (681-688)

Sugár I, Zhai X, Boldyrev I, Molotkovsky J, Brockman H and Brown R (2010). Characterization of the lateral distribution of fluorescent lipid in binary-constituent lipid monolayers by principal component analysis, Journal of Biomedical Imaging , 2010 , (1-9), Online publication date: 1-Jan-2010 .

Fan J, Samworth R and Wu Y (2009). Ultrahigh Dimensional Feature Selection: Beyond The Linear Model, The Journal of Machine Learning Research , 10 , (2013-2038), Online publication date: 1-Dec-2009 .

Aggarwal V, George A, Yalamanchili K, Yoon C, Lam H and Stitt G Bridging parallel and reconfigurable computing with multilevel PGAS and SHMEM+ Proceedings of the Third International Workshop on High-Performance Reconfigurable Computing Technology and Applications, (47-54)

Tuia D and Camps-Valls G Recent advances in remote sensing image processing Proceedings of the 16th IEEE international conference on Image processing, (3661-3664)

Floares A Using computational intelligence to develop intelligent clinical decision support systems Proceedings of the 6th international conference on Computational intelligence methods for bioinformatics and biostatistics, (266-275)

Balaguer B, Carpin S, Balakirsky S and Visser A Evaluation of RoboCup maps Proceedings of the 9th Workshop on Performance Metrics for Intelligent Systems, (217-222)

Rodner E and Denzler J Learning with Few Examples by Transferring Feature Relevance Proceedings of the 31st DAGM Symposium on Pattern Recognition - Volume 5748, (252-261)

Pevný T, Bas P and Fridrich J Steganalysis by subtractive pixel adjacency matrix Proceedings of the 11th ACM workshop on Multimedia and security, (75-84)

Li Y and Lu B (2009). Feature selection based on loss-margin of nearest neighbor classification, Pattern Recognition , 42 :9 , (1914-1921), Online publication date: 1-Sep-2009 .

Malakasiotis P Paraphrase recognition using machine learning to combine similarity measures Proceedings of the ACL-IJCNLP 2009 Student Research Workshop, (27-35)

Floares A Liver i-BiopsyTM and the Corresponding Intelligent Fibrosis Scoring Systems Computational Intelligence Methods for Bioinformatics and Biostatistics, (253-264)

Floares A Intelligent clinical decision supports for interferon treatment in chronic hepatitis C and B based on i-biopsyTM Proceedings of the 2009 international joint conference on Neural Networks, (2269-2274)

Bolón-Canedo V, Sánchez-Maroño N and Alonso-Betanzos A A combination of discretization and filter methods for improving classification performance in KDD Cup 99 dataset Proceedings of the 2009 international joint conference on Neural Networks, (305-312)

Vatolkin I, Theimer W and Rudolph G Design and comparison of different evolution strategies for feature selection and consolidation in music classification Proceedings of the Eleventh conference on Congress on Evolutionary Computation, (174-181)

Mac Parthaláin N and Shen Q (2009). Exploring the boundary region of tolerance rough sets for feature selection, Pattern Recognition , 42 :5 , (655-667), Online publication date: 1-May-2009 .

Vieira A, Duarte J, Ribeiro B and Neves J Accurate prediction of financial distress of companies with machine learning algorithms Proceedings of the 9th international conference on Adaptive and natural computing algorithms, (569-576)

Ribeiro B, Silva C, Vieira A and Neves J Extracting discriminative features using non-negative matrix factorization in financial distress data Proceedings of the 9th international conference on Adaptive and natural computing algorithms, (537-547)

Vieira A, Duarte J, Ribeiro B and Neves J Accurate Prediction of Financial Distress of Companies with Machine Learning Algorithms Proceedings of the 2009 conference on Adaptive and Natural Computing Algorithms - Volume 5495, (569-576)

Ribeiro B, Silva C, Vieira A and Neves J Extracting Discriminative Features Using Non-negative Matrix Factorization in Financial Distress Data Proceedings of the 2009 conference on Adaptive and Natural Computing Algorithms - Volume 5495, (537-547)

Kasabov N Integrative probabilistic evolving spiking neural networks utilising quantum inspired evolutionary algorithm Proceedings of the 15th international conference on Advances in neuro-information processing - Volume Part I, (3-13)

Jankowski A, Peters J, Skowron A and Stepaniuk J (2008). Optimization in Discovery of Compound Granules, Fundamenta Informaticae , 85 :1-4 , (249-265), Online publication date: 20-Sep-2008 .

Yom-Tov E, Tzoref R, Ur S and Hoory S Automatic Debugging of Concurrent Programs through Active Sampling of Low Dimensional Random Projections Proceedings of the 23rd IEEE/ACM International Conference on Automated Software Engineering, (307-316)

Vatolkin I and Theimer W Optimization of Feature Processing Chain in Music Classification by Evolution Strategies Proceedings of the 10th International Conference on Parallel Problem Solving from Nature --- PPSN X - Volume 5199, (1150-1159)

Jiang Y, Cukic B and Menzies T Can data transformation help in the detection of fault-prone modules? Proceedings of the 2008 workshop on Defects in large software systems, (16-20)

Claeskens G, Croux C and Van Kerckhoven J (2008). An Information Criterion for Variable Selection in Support Vector Machines, The Journal of Machine Learning Research , 9 , (541-558), Online publication date: 1-Jun-2008 .

Xu L, Hutter F, Hoos H and Leyton-Brown K (2008). SATzilla, Journal of Artificial Intelligence Research , 32 :1 , (565-606), Online publication date: 1-May-2008 .

Rokach L (2008). Genetic algorithm-based feature set partitioning for classification problems, Pattern Recognition , 41 :5 , (1676-1700), Online publication date: 1-May-2008 .

Guillen A, Sovilj D, Lendasse A, Mateo F and Rojas I (2008). Minimising the delta test for variable selection in regression problems, International Journal of High Performance Systems Architecture , 1 :4 , (269-281), Online publication date: 1-Mar-2008 .

Jankowski A, Peters J, Skowron A and Stepaniuk J (2008). Optimization in Discovery of Compound Granules, Fundamenta Informaticae , 85 :1-4 , (249-265), Online publication date: 1-Jan-2008 .

Sánchez-Maroño N, Alonso-Betanzos A and Tombilla-Sanromán M Filter methods for feature selection Proceedings of the 8th international conference on Intelligent data engineering and automated learning, (178-187)

Sánchez-Maroño N, Alonso-Betanzos A and Tombilla-Sanromán M Filter Methods for Feature Selection – A Comparative Study Intelligent Data Engineering and Automated Learning - IDEAL 2007, (178-187)

Peters J and Ramanna S Feature selection Proceedings of the 3rd ECML/PKDD international conference on Mining complex data, (57-71)

Peters J and Ramanna S Feature selection Proceedings of the Third International Conference on Mining Complex Data, (57-71)

Puchala E and Rewak A The feature extraction procedure for pattern recognition with learning using genetic algorithm Proceedings of the 7th WSEAS International Conference on Simulation, Modelling and Optimization, (32-36)

Schaffernicht E, Stephan V and Groß H An efficient search strategy for feature selection using Chow-Liu trees Proceedings of the 17th international conference on Artificial neural networks, (190-199)

Jursa R Variable selection for wind power prediction using particle swarm optimization Proceedings of the 9th annual conference on Genetic and evolutionary computation, (2059-2065)

Gagné C, Sebag M, Schoenauer M and Tomassini M Ensemble learning for free with evolutionary algorithms? Proceedings of the 9th annual conference on Genetic and evolutionary computation, (1782-1789)

Pranckeviciene E and Somorjai R Liknon Feature Selection for Microarrays Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory, (580-587)

Peters J Near sets Proceedings of the 2nd international conference on Rough sets and knowledge technology, (22-33)

Kaiser D Automatic feature extraction for autonomous general game playing agents Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems, (1-7)

Lim S, Wang L and DeJong G Explanation-based feature construction Proceedings of the 20th international joint conference on Artifical intelligence, (931-936)

Peters J (2007). Near Sets. Special Theory about Nearness of Objects, Fundamenta Informaticae , 75 :1-4 , (407-433), Online publication date: 1-Jan-2007 .

Zhou J, Foster D, Stine R and Ungar L (2006). Streamwise Feature Selection, The Journal of Machine Learning Research , 7 , (1861-1885), Online publication date: 1-Dec-2006 .

Lemaire V and Féraud R Driven forward features selection Proceedings of the 13th international conference on Neural Information Processing - Volume Part II, (693-702)

Kurzynski M and Puchala E The optimal feature extraction procedure for statistical pattern recognition Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part III, (1210-1215)

Rogers J and Gunn S Identifying feature relevance using a random forest Proceedings of the 2005 international conference on Subspace, Latent Structure and Feature Selection, (173-184)

Wurst M Multi-agent learning by distributed feature extraction Proceedings of the 5th , 6th and 7th European conference on Adaptive and learning agents and multi-agent systems: adaptation and multi-agent learning, (239-254)

ElNakieb Y, Barnes G, El-Baz A, Soliman A, Mahmoud A, Dekhil O, Shalaby A, Ghazal M, Khalil A, Switala A and Keynton R Autism Spectrum Disorder Diagnosis framework using Diffusion Tensor Imaging 2019 IEEE International Conference on Imaging Systems and Techniques (IST), (1-5)

Yang L, Chen Y, Pan H, Ding D, Xue G, Kong L, Yu J and Li M MagPrint: Deep Learning Based User Fingerprinting Using Electromagnetic Signals IEEE INFOCOM 2020 - IEEE Conference on Computer Communications, (696-705)

Boullé M Towards Automatic Feature Construction for Supervised Classification Machine Learning and Knowledge Discovery in Databases, (181-196)