Amparo Alonso-Betanzos

发表

A scalable saliency-based Feature selection method with instance level information

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, João Gama, 2019, Knowl. Based Syst..

Developing an electrical distribution monitoring system

Amparo Alonso-Betanzos, M.C.S.-C. Roldan, J. E. Arias-Rodriguez, 1997 .

Dealing with inter-expert variability in Retinopathy of Prematurity through machine learning

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Deniz Erdogmus, 2015 .

A Regularized Learning Method for Neural Networks Based on Sensitivity Analysis

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, Beatriz Pérez-Sánchez, 2008, ESANN.

A new method for sleep apnea classification using wavelets and feedforward neural networks

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, Bertha Guijarro-Berdiñas, 2005, Artif. Intell. Medicine.

Trends in Practical Applications of Agents, Multi-Agent Systems and Sustainability

Javier Bajo, Vicente Julián, Amparo Alonso-Betanzos, 2015 .

A new supervised local modelling classifier based on information theory

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, David Martínez-Rego, 2009, 2009 International Joint Conference on Neural Networks.

Selection of the Best Base Classifier in One-Versus-One Using Data Complexity Measures

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Laura Morán-Fernández, 2016, CAEPIA.

Exact Incremental Learning for a Single Non-linear Neuron Based on Taylor Expansion and Greville Formula

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, David Martínez-Rego, 2013, CAEPIA.

ESANN 2011 19th European Symposium on Artificial Neural Networks

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Jose C. Principe, 2011 .

One-Class Convex Hull-Based Algorithm for Classification in Distributed Environments

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, Diego Fernández-Francos, 2020, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

An intelligent system for forest fire risk prediction and fire fighting management in Galicia

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, Bertha Guijarro-Berdiñas, 2003, Expert Syst. Appl..

One-class classification algorithm based on convex hull

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, Diego Fernández-Francos, 2016, ESANN.

On the scalability of feature selection methods on high-dimensional data

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Bertha Guijarro-Berdiñas, 2017, Knowledge and Information Systems.

Influence of internal values and social networks for achieving sustainable organizations

Amparo Alonso-Betanzos, Tony Craig, Oscar Fontenla-Romero, 2014, ECAI.

Feature selection for high-dimensional data

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2016, Progress in Artificial Intelligence.

An ensemble of filters and classifiers for microarray data classification

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2012, Pattern Recognit..

On the effectiveness of discretization on gene selection of microarray data

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

Intelligent analysis and pattern recognition in cardiotocographic signals using a tightly coupled hybrid system

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, Bertha Guijarro-Berdiñas, 2002, Artif. Intell..

A combination of discretization and filter methods for improving classification performance in KDD Cup 99 dataset

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2009, 2009 International Joint Conference on Neural Networks.

Centralized vs. distributed feature selection methods based on data complexity measures

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Laura Moran-Fernandez, 2017, Knowl. Based Syst..

Scalable approximate k-NN Graph construction based on Locality Sensitive Hashing

Amparo Alonso-Betanzos, Leslie Kanthan, David Martínez-Rego, 2017, ESANN.

Multithreaded and Spark parallelization of feature selection filters

Sabela Ramos, Verónica Bolón-Canedo, Amparo Alonso-Betanzos, 2016, J. Comput. Sci..

Functional Network Topology Learning and Sensitivity Analysis Based on ANOVA Decomposition

Amparo Alonso-Betanzos, Enrique F. Castillo, Noelia Sánchez-Maroño, 2007, Neural Computation.

Shear strength prediction using dimensional analysis and functional networks

Amparo Alonso-Betanzos, Enrique F. Castillo, Oscar Fontenla-Romero, 2004, ESANN.

Volume, variety and velocity in Data Science

Jose Miguel Puerta, José A. Gámez, Amparo Alonso-Betanzos, 2017, Knowledge-Based Systems.

Feature Selection in DNA Microarray Classification

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2015 .

A Global Optimum Approach for One-Layer Neural Networks

Amparo Alonso-Betanzos, Enrique F. Castillo, Oscar Fontenla-Romero, 2002, Neural Computation.

A Measure of Noise Immunity for Functional Networks

Amparo Alonso-Betanzos, Enrique F. Castillo, Oscar Fontenla-Romero, 2001, IWANN.

A Functional-Neural Network for Post-Nonlinear Independent Component Analysis

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, Bertha Guijarro-Berdiñas, 2001, IWANN.

Scalability Analysis of ANN Training Algorithms with Feature Selection

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Bertha Guijarro-Berdiñas, 2011, CAEPIA.

Modeling consumption of contents and advertising in online newspapers

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, David Martínez-Rego, 2014, ESANN.

FOETOS in clinical practice: A retrospective analysis of its performance

Amparo Alonso-Betanzos, Vicente Moret-Bonillo, Lawrence D. Devoe, 1989, Artif. Intell. Medicine.

Up-to-Date Feature Selection Methods for Scalable and Efficient Machine Learning

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2013 .

Wavefront Marching Methods: A Unified Algorithm to Solve Eikonal and Static Hamilton-Jacobi Equations

Amparo Alonso-Betanzos, Brais Cancela, Amparo Alonso-Betanzos, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

A Time Efficient Approach for Distributed Feature Selection Partitioning by Features

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Laura Moran-Fernandez, 2015, CAEPIA.

An expert system approach to antenatal assessment

Amparo Alonso-Betanzos, Lawrence D. Devoe, Betha Guijarro-Berdinas, 1996 .

A Log Analyzer Agent for Intrusion Detection in a Multi-Agent System

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, Iago Porto-Díaz, 2010, KES.

Ensemble feature selection: Homogeneous and heterogeneous approaches

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Iago Porto-Díaz, 2017, Knowl. Based Syst..

Towards the implementation of intelligent structures in intensive care monitoring: the advantages of the symbolic pre-processing

Amparo Alonso-Betanzos, John R. Searle, Vicente Moret-Bonillo, 1990, ACM-SE 28.

An insight on complexity measures and classification in microarray data

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Laura Moran-Fernandez, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

Ensemble Feature Selection for Rankings of Features

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Iago Porto-Díaz, 2015, IWANN.

Reducing dimensionality in a database of sleep EEG arousals

Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, Diego Álvarez-Estévez, 2011, Expert Syst. Appl..

Dealing with inter-expert variability in retinopathy of prematurity: A machine learning approach

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Deniz Erdogmus, 2015, Comput. Methods Programs Biomed..

Combining Feature Selection and Local Modelling in the KDD Cup 99 Dataset

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, David Martínez-Rego, 2009, ICANN.

A scalable saliency-based Feature selection method with instance level information

Amparo Alonso-Betanzos, Brais Cancela, Ver'onica Bol'on-Canedo, 2019 .

Efficiency of local models ensembles for time series prediction

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, David Martínez-Rego, 2011, Expert Syst. Appl..

Testing Different Ensemble Configurations for Feature Selection

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Borja Seijo-Pardo, 2017, Neural Processing Letters.

A Comparative Study of Local Classifiers Based on Clustering Techniques and One-Layer Neural Networks

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, Yuridia Gago-Pallares, 2007, IDEAL.

An Information Theory-Based Feature Selection Framework for Big Data Under Apache Spark

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Francisco Herrera, 2018, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

Data complexity measures for analyzing the effect of SMOTE over microarrays

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Laura Morán-Fernández, 2016, ESANN.

A Neural Network Approach for Forestal Fire Risk Estimation

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, Bertha Guijarro-Berdiñas, 2002, ECAI.

Fast‐mRMR: Fast Minimum Redundancy Maximum Relevance Algorithm for High‐Dimensional Big Data

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Francisco Herrera, 2017, Int. J. Intell. Syst..

Recent advances and emerging challenges of feature selection in the context of big data

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2015, Knowl. Based Syst..

An Information Theoretic Feature Selection Framework for Big Data under Apache Spark pdf

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Francisco Herrera, 2016, ArXiv.

Automatic bearing fault diagnosis based on one-class ν-SVM

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, David Martínez-Rego, 2013, Comput. Ind. Eng..

Toward the scalability of neural networks through feature selection

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Bertha Guijarro-Berdiñas, 2013, Expert Syst. Appl..

A measure of fault tolerance for functional networks

Amparo Alonso-Betanzos, Enrique F. Castillo, Oscar Fontenla-Romero, 2004, Neurocomputing.

Information Theoretic Learning and local modeling for binary and multiclass classification

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, David Martínez-Rego, 2012, Progress in Artificial Intelligence.

A new convex objective function for the supervised learning of single-layer neural networks

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, Beatriz Pérez-Sánchez, 2010, Pattern Recognit..

A Wrapper Method for Feature Selection in Multiple Classes Datasets

Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, Rosa M. Calvo-Estévez, 2009, IWANN.

Multiclass classifiers vs multiple binary classifiers using filters for feature selection

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

A factorization approach to evaluate open-response assignments in MOOCs using preference learning on peer assessments

Amparo Alonso-Betanzos, Alicia Troncoso Lora, Oscar Luaces, 2015, Knowl. Based Syst..

Dealing with heterogeneity in the context of distributed feature selection for classification

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, José Luis Morillo-Salas, 2020, Knowl. Inf. Syst..

Including Content-Based Methods in Peer-Assessment of Open-Response Questions

Amparo Alonso-Betanzos, Alicia Troncoso Lora, Oscar Luaces, 2015, 2015 IEEE International Conference on Data Mining Workshop (ICDMW).

Analysis and evaluation of hard and fuzzy clustering segmentation techniques in burned patient images

Amparo Alonso-Betanzos, Bernardino Arcay Varela, Alfonso Castro Martínez, 2000, Image Vis. Comput..

An Agent-Based Model for Simulating Environmental Behavior in an Educational Organization

Amparo Alonso-Betanzos, Tony Craig, Oscar Fontenla-Romero, 2014, Neural Processing Letters.

A unified pipeline for online feature selection and classification

Amparo Alonso-Betanzos, Bertha Guijarro-Berdiñas, Noelia Sánchez-Maroño, 2016, Expert Syst. Appl..

Large scale anomaly detection in mixed numerical and categorical input spaces

Amparo Alonso-Betanzos, Bertha Guijarro-Berdiñas, David Martínez-Rego, 2019, Inf. Sci..

Exploring the consequences of distributed feature selection in DNA microarray data

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Data classification using an ensemble of filters

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2014, Neurocomputing.

E2E-FS: An End-to-End Feature Selection Method for Neural Networks pdf

Amparo Alonso-Betanzos, Brais Cancela, Ver'onica Bol'on-Canedo, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

On the use of different base classifiers in multiclass problems

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Laura Moran-Fernandez, 2017, Progress in Artificial Intelligence.

A Method for Time Series Prediction using a Combination of Linear Models

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, David Martínez-Rego, 2008, ESANN.

Conversion methods for symbolic features: A comparison applied to an intrusion detection problem

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, Elena Hernández-Pereira, 2009, Expert Syst. Appl..

Insights into distributed feature ranking

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Gavin Brown, 2019, Inf. Sci..

A distributed wrapper approach for feature selection

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2013, ESANN.

A Fast Classification Algorithm Based on Local Models

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, Sabela Platero-Santos, 2006, IDEAL.

Do we need hundreds of classifiers or a good feature selection?

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Laura Morán-Fernández, 2020, ESANN.

Applying statistical, uncertainty-based and connectionist approaches to the prediction of fetal outcome: a comparative study

Amparo Alonso-Betanzos, Vicente Moret-Bonillo, Eduardo Mosqueira-Rey, 1999, Artif. Intell. Medicine.

On the behavior of feature selection methods dealing with noise and relevance over synthetic scenarios

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2011, The 2011 International Joint Conference on Neural Networks.

Feature Selection Based on Sensitivity Analysis

Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2007, CAEPIA.

Linear-least-squares initialization of multilayer perceptrons through backpropagation of the desired response

Amparo Alonso-Betanzos, Enrique F. Castillo, Deniz Erdogmus, 2005, IEEE Transactions on Neural Networks.

Preprocessing in Big Data: New challenges for discretization and feature selection

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2017 .

Modelling Engineering Problems Using Dimensional Analysis for Feature Extraction

Amparo Alonso-Betanzos, Enrique F. Castillo, Oscar Fontenla-Romero, 2005, ICANN.

A comparison of performance of K-complex classification methods using feature selection

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2016, Inf. Sci..

Scalability Analysis of mRMR for Microarray Data

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Diego Rego-Fernández, 2014, ICAART.

Local Modeling Classifier for Microarray Gene-Expression Data

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Oscar Fontenla-Romero, 2010, ICANN.

An Agent-Based Prototype for Enhancing Sustainability Behavior at an Academic Environment

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Tony Craig, 2012, PAAMS.

Recent Advances in Ensembles for Feature Selection

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Amparo Alonso-Betanzos, 2018, Intelligent Systems Reference Library.

A review of microarray datasets and applied feature selection methods

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, José Manuel Benítez, 2014, Inf. Sci..

A distributed approach for classification using distance metrics

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Laura Morán-Fernández, 2017, ESANN.

Learning on Vertically Partitioned Data based on Chi-square Feature Selection and Naive Bayes Classification

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Bertha Guijarro-Berdiñas, 2014, ICAART.

Self-organizing maps and functional networks for local dynamic modeling

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, Bertha Guijarro-Berdiñas, 2003, ESANN.

One-class classifier based on extreme value statistics

Amparo Alonso-Betanzos, José Carlos Príncipe, Oscar Fontenla-Romero, 2012, ESANN.

A Critical Review of Feature Selection Methods

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2015 .

A robust incremental learning method for non-stationary environments

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, Beatriz Pérez-Sánchez, 2011, Neurocomputing.

Combining functional networks and sensitivity analysis as wrapper method for feature selection

Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2011, Expert Syst. Appl..

Scalability analysis of lter-based methods for feature selection

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Bertha Guijarro-Berdiñas, 2012 .

A Minimum Volume Covering Approach with a Set of Ellipsoids

Amparo Alonso-Betanzos, Enrique F. Castillo, Oscar Fontenla-Romero, 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Fault detection via recurrence time statistics and one-class classification

Amparo Alonso-Betanzos, José Carlos Príncipe, Oscar Fontenla-Romero, 2016, Pattern Recognit. Lett..

Analysis of imputation bias for feature selection with missing data

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Julie Josse, 2018, ESANN.

Distributed classification based on distances between probability distributions in feature space

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Pablo Montero-Manso, 2019, Inf. Sci..

Regression Tree Based Explanation for Anomaly Detection Algorithm

Amparo Alonso-Betanzos, Carlos Eiras-Franco, Iñigo López-Riobóo Botana, 2020 .

A review of feature selection methods on synthetic data

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2013, Knowledge and Information Systems.

Biases in feature selection with missing data

Isabelle Guyon, Verónica Bolón-Canedo, Amparo Alonso-Betanzos, 2019, Neurocomputing.

Fault Prognosis of Mechanical Components Using On-Line Learning Neural Networks

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, Beatriz Pérez-Sánchez, 2010, ICANN.

Recursive Least Squares for an Entropy Regularized MSE Cost Function

Amparo Alonso-Betanzos, Deniz Erdogmus, José Carlos Príncipe, 2003, ESANN.

A Bayesian Neural Network Approach for Sleep Apnea Classification

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, Bertha Guijarro-Berdiñas, 2003, AIME.

Performance evaluation of unsupervised techniques in cyber-attack anomaly detection

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, João Carneiro, 2019, Journal of Ambient Intelligence and Humanized Computing.

A Misuse Detection Agent for Intrusion Detection in a Multi-agent Architecture

Amparo Alonso-Betanzos, Eduardo Mosqueira-Rey, Belén Baldonedo del Río, 2007, KES-AMSTA.

A Comparative Analysis of the Neonatal Prognosis Problem Using Artificial Neural Networks, Statistical Techniques and Certainty Management Techniques

Amparo Alonso-Betanzos, Eduardo Mosqueira-Rey, Belén Baldonedo del Río, 1997, IWANN.

A tool for agent communication in Mozart/Oz

Amparo Alonso-Betanzos, Bertha Guijarro-Berdiñas, Juan A. Suárez-Romero, 2005, IEEE/WIC/ACM International Conference on Intelligent Agent Technology.

Advances in Artificial Intelligence: 15th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2013, Madrid, September 17-20, ... / Lecture Notes in Artificial Intelligence)

Juan M. Corchado, Amparo Alonso-Betanzos, Concha Bielza, 2013 .

Ensembles for feature selection: A review and future trends

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Amparo Alonso-Betanzos, 2019, Inf. Fusion.

Toward an ensemble of filters for classification

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2011, 2011 11th International Conference on Intelligent Systems Design and Applications.

Distributed Correlation-Based Feature Selection in Spark

Amparo Alonso-Betanzos, Luis de Marcos, Raul-Jose Palma-Mendoza, 2019, Inf. Sci..

A Neural Network Approach to the Classification of Decelerative Cardiotocographic Patterns in the CAFE Project

Amparo Alonso-Betanzos, Bertha Guijarro-Berdiñas, Olga Fernández-Chaves, 1998, NC.

Empirical evaluation of a hybrid intelligent monitoring system using different measures of effectiveness

Amparo Alonso-Betanzos, Bertha Guijarro-Berdiñas, Amparo Alonso-Betanzos, 2002, Artif. Intell. Medicine.

Machine learning for medical applications

Beatriz Remeseiro, Verónica Bolón-Canedo, Amparo Alonso-Betanzos, 2016, ESANN.

Using Data Complexity Measures for Thresholding in Feature Selection Rankers

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Borja Seijo-Pardo, 2016, CAEPIA.

A Snort-based agent for a JADE multi-agent intrusion detection system

Amparo Alonso-Betanzos, Bertha Guijarro-Berdiñas, Eduardo Mosqueira-Rey, 2009, Int. J. Intell. Inf. Database Syst..

On the use of machine learning techniques for the analysis of spontaneous reactions in automated hearing assessment

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Manuel G. Penedo, 2015, ESANN.

Linear Least-Squares Based Methods for Neural Networks Learning

Amparo Alonso-Betanzos, Enrique F. Castillo, Deniz Erdogmus, 2003, ICANN.

Functional Networks and Analysis of Variance for Feature Selection

Amparo Alonso-Betanzos, Enrique F. Castillo, Noelia Sánchez-Maroño, 2006, IDEAL.

Stream change detection via passive-aggressive classification and Bernoulli CUSUM

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, David Martínez-Rego, 2015, Inf. Sci..

Detection of Fetal Heart Rate Accelerations and Decelerations Using Artificial Neural Networks

Amparo Alonso-Betanzos, José Carlos Príncipe, Oscar Fontenla-Romero, 1998, NC.

Recovering Missing Data with Functional and Bayesian Networks

Amparo Alonso-Betanzos, Enrique F. Castillo, Noelia Sánchez-Maroño, 2003, IWANN.

The NST-EXPERT project: the need to evolve

Amparo Alonso-Betanzos, Bertha Guijarro-Berdiñas, Vicente Moret-Bonillo, 1995, Artif. Intell. Medicine.

A JADE-Based Framework for Developing Evolutionary Multi-Agent Systems

Amparo Alonso-Betanzos, Bertha Guijarro-Berdiñas, Santiago Fernández-Lorenzo, 2009, PAAMS.

A Very Fast Learning Method for Neural Networks Based on Sensitivity Analysis

Amparo Alonso-Betanzos, Enrique F. Castillo, Oscar Fontenla-Romero, 2006, J. Mach. Learn. Res..

A Distributed Feature Selection Approach Based on a Complexity Measure

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2015, IWANN.

An Approach to Intensive Care Monitoring That Combines Deterministic And Heuristic Techniques

Amparo Alonso-Betanzos, John R. Searle, Vicente Moret-Bonillo, 1990 .

Algorithmic challenges in big data analytics

Beatriz Remeseiro, Verónica Bolón-Canedo, Amparo Alonso-Betanzos, 2017, ESANN.

A New Wrapper Method for Feature Subset Selection

Amparo Alonso-Betanzos, Enrique F. Castillo, Noelia Sánchez-Maroño, 2005, ESANN.

An Add-On for Managing Behaviours with Priority in JADE

Amparo Alonso-Betanzos, Bertha Guijarro-Berdiñas, Juan A. Suárez-Romero, 2006, 2006 IEEE/WIC/ACM International Conference on Intelligent Agent Technology.

Introduction to High-Dimensionality

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2015 .

Distributed feature selection: An application to microarray data classification

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2015, Appl. Soft Comput..

Foundations of Feature Selection

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2015 .

Feature selection with limited bit depth mutual information for portable embedded systems

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Gavin Brown, 2020, Knowl. Based Syst..

Mutual information for improving the efficiency of the SCH algorithm

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, Gavin Brown, 2017, ESANN.

A study of performance on microarray data sets for a classifier based on information theoretic learning

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Oscar Fontenla-Romero, 2011, Neural Networks.

Power wind mill fault detection via one-class ν-SVM vibration signal analysis

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, David Martínez-Rego, 2011, The 2011 International Joint Conference on Neural Networks.

Accelerating the convergence speed of neural networks learning methods using least squares

Amparo Alonso-Betanzos, Enrique F. Castillo, Deniz Erdogmus, 2003, ESANN.

Local Modeling Using Self-Organizing Maps and Single Layer Neural Networks

Amparo Alonso-Betanzos, Enrique F. Castillo, José Carlos Príncipe, 2002, ICANN.

Optimizing novelty and diversity in recommendations

Amparo Alonso-Betanzos, David Martínez-Rego, Oscar Luaces, 2018, Progress in Artificial Intelligence.

A Decision-Making Model for Environmental Behavior in Agent-Based Modeling

Amparo Alonso-Betanzos, Tony Craig, Oscar Fontenla-Romero, 2013, IWANN.

Adaptive pattern recognition in the analysis of cardiotocographic records

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, Bertha Guijarro-Berdiñas, 2001, IEEE Trans. Neural Networks.

Special issue on medical applications of expert systems

Amparo Alonso-Betanzos, Vicente Moret-Bonillo, 1993 .

Can classification performance be predicted by complexity measures? A study using microarray data

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Laura Moran-Fernandez, 2017, Knowledge and Information Systems.

Classification of computer intrusions using functional networks. A comparative study

Amparo Alonso-Betanzos, Beatriz Pérez-Sánchez, Noelia Sánchez-Maroño, 2007, ESANN.

A Hybrid Intelligent System for the Preprocessing of Fetal Heart Rate Signals in Antenatal Testing

Amparo Alonso-Betanzos, Bertha Guijarro-Berdiñas, Olga Fernández-Chaves, 1997, IWANN.

An Improved Version of the Wrapper Feature Selection Method Based on Functional Decomposition

Amparo Alonso-Betanzos, Beatriz Pérez-Sánchez, Noelia Sánchez-Maroño, 2007, ICANN.

Feature Selection

Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, Amparo Alonso-Betanzos, 2009, Encyclopedia of Artificial Intelligence.

An Auto-learning System for the Classification of Fetal Heart Rate Decelerative Patterns

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, Bertha Guijarro-Berdiñas, 2001, IWANN.

On developing an automatic threshold applied to feature selection ensembles

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Borja Seijo-Pardo, 2018, Inf. Fusion.

EECB: a knowledge elicitation tool based on repertory grid and city block metric

Amparo Alonso-Betanzos, José R. Paramá, Nieves R. Brisaboa, 1998 .

Filter Methods for Feature Selection - A Comparative Study

Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, María Tombilla-Sanromán, 2007, IDEAL.

A framework for cost-based feature selection

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2014, Pattern Recognit..

Paving the way for providing teaching feedback in automatic evaluation of open response assignments

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Oscar Luaces, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Data discretization: taxonomy and big data challenge

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Francisco Herrera, 2016, WIREs Data Mining Knowl. Discov..

A New Learning Method for Single Layer Neural Networks Based on a Regularized Cost Function

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, Bertha Guijarro-Berdiñas, 2003, IWANN.

Symbolic, Neural and Neuro-fuzzy Approaches to Pattern Recognition in Cardiotocograms

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, Bertha Guijarro-Berdiñas, 2002, Advances in Computational Intelligence and Learning.

Designing Decision Trees for Representing Sustainable Behaviours in Agents

Amparo Alonso-Betanzos, Tony Craig, Oscar Fontenla-Romero, 2015, PAAMS.

Information analysis and validation of intelligent monitoring systems in intensive care units

Amparo Alonso-Betanzos, Vicente Moret-Bonillo, Eduardo Mosqueira-Rey, 1997, IEEE Transactions on Information Technology in Biomedicine.

Application of Feature Selection to Real Problems

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2015 .

mC-ReliefF - An Extension of ReliefF for Cost-based Feature Selection

Beatriz Remeseiro, Verónica Bolón-Canedo, Amparo Alonso-Betanzos, 2014, ICAART.

PATRICIA: An expert system that incorporates a patient-oriented approach for the management of ICU patients

Amparo Alonso-Betanzos, Vicente Moret-Bonillo, Edward J. Truemper, 1992, 1992 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Feature selection and classification in multiple class datasets: An application to KDD Cup 99 dataset

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2011, Expert Syst. Appl..

Using a feature selection ensemble on DNA microarray datasets

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Borja Seijo-Pardo, 2016, ESANN.

Nonlinear single layer neural network training algorithm for incremental, nonstationary and distributed learning scenarios

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, David Martínez-Rego, 2012, Pattern Recognit..

Feature Selection and Conversion Methods in KDD Cup 99 Dataset: A Comparison of Performance

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Noelia Sánchez-Maroño, 2010 .

Real-Time Tear Film Classification Through Cost-Based Feature Selection

Beatriz Remeseiro, Verónica Bolón-Canedo, Amparo Alonso-Betanzos, 2015, Trans. Comput. Collect. Intell..

Statistical dependence measure for feature selection in microarray datasets

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, José Carlos Príncipe, 2011, ESANN.

A delayed Elastic-Net approach for performing adversarial attacks

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Brais Cancela, 2021, 2020 25th International Conference on Pattern Recognition (ICPR).

Can data placement be effective for Neural Networks classification tasks? Introducing the Orthogonal Loss

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Brais Cancela, 2021, 2020 25th International Conference on Pattern Recognition (ICPR).

How important is data quality? Best classifiers vs best features

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Laura Morán-Fernández, 2021, Neurocomputing.

A connectionist approach to predict antenatal outcome

Amparo Alonso-Betanzos, Vicente Moret-Bonillo, Alejandro Pazos, 1992, 1992 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

A New Initialization Method for Neural Networks Using Sensitivity Analysis

Amparo Alonso-Betanzos, Oscar Fontenla-Romero, Beatriz Pérez-Sánchez, 2022 .