| OCEAn: Ordinal classification with an ensemble approach | 0 | 0.34 | 2021 |
| An Experimental Review On Deep Learning Architectures For Time Series Forecasting | 2 | 0.64 | 2021 |
| Feature Selection on Spatio-Temporal Data for Solar Irradiance Forecasting | 0 | 0.34 | 2021 |
| Enhancing object detection for autonomous driving by optimizing anchor generation and addressing class imbalance | 0 | 0.34 | 2021 |
| Filter-based feature selection in the context of evolutionary neural networks in supervised machine learning | 0 | 0.34 | 2020 |
| A Preliminary Study on Deep Transfer Learning Applied to Image Classification for Small Datasets. | 1 | 0.35 | 2020 |
| Coronavirus Optimization Algorithm: A bioinspired metaheuristic based on the COVID-19 propagation model | 2 | 0.38 | 2020 |
| On the performance of deep learning models for time series classification in streaming | 0 | 0.34 | 2020 |
| Asynchronous Dual-Pipeline Deep Learning Framework For Online Data Stream Classification | 0 | 0.34 | 2020 |
| Autoencoded Dna Methylation Data To Predict Breast Cancer Recurrence: Machine Learning Models And Gene-Weight Significance | 0 | 0.34 | 2020 |
| Creation of Synthetic Data with Conditional Generative Adversarial Networks. | 0 | 0.34 | 2019 |
| A Framework for Evaluating Land Use and Land Cover Classification Using Convolutional Neural Networks. | 0 | 0.34 | 2019 |
| A Novel Ensemble Method for Electric Vehicle Power Consumption Forecasting: Application to the Spanish System | 0 | 0.34 | 2019 |
| External clustering validity index based on chi-squared statistical test. | 0 | 0.34 | 2019 |
| Semi-wrapper feature subset selector for feed-forward neural networks: applications to binary and multi-class classification problems | 0 | 0.34 | 2019 |
| A novel approach to forecast urban surface-level ozone considering heterogeneous locations and limited information. | 0 | 0.34 | 2018 |
| Smartfd: A Real Big Data Application For Electrical Fraud Detection | 0 | 0.34 | 2018 |
| Impact of Auto-evaluation Tests as Part of the Continuous Evaluation in Programming Courses | 0 | 0.34 | 2018 |
| Low Dimensionality or Same Subsets as a Result of Feature Selection: An In-Depth Roadmap. | 1 | 0.36 | 2017 |
| Applications of Computational Intelligence in Time Series. | 0 | 0.34 | 2017 |
| Volume, variety and velocity in Data Science. | 1 | 0.35 | 2017 |
| Obtaining optimal quality measures for quantitative association rules | 3 | 0.36 | 2016 |
| Improving a multi-objective evolutionary algorithm to discover quantitative association rules | 1 | 0.34 | 2016 |
| Accuracy Increase On Evolving Product Unit Neural Networks Via Feature Subset Selection | 1 | 0.36 | 2016 |
| A multi-scale smoothing kernel for measuring time-series similarity | 3 | 0.37 | 2015 |
| A comparison of machine learning regression techniques for LiDAR-derived estimation of forest variables | 5 | 0.56 | 2015 |
| Enhancing the scalability of a genetic algorithm to discover quantitative association rules in large-scale datasets | 14 | 0.46 | 2015 |
| Data Cleansing Meets Feature Selection: A Supervised Machine Learning Approach | 0 | 0.34 | 2015 |
| Tackling Ant Colony Optimization Meta-Heuristic As Search Method In Feature Subset Selection Based On Correlation Or Consistency Measures | 2 | 0.38 | 2014 |
| Preliminary comparison of techniques for dealing with imbalance in software defect prediction | 17 | 0.57 | 2014 |
| A Comparative Study of Machine Learning Regression Methods on LiDAR Data: A Case Study. | 0 | 0.34 | 2013 |
| ra A Sensitivity Analysis for Quality Measures of Quantitative Association Rules. | 0 | 0.34 | 2013 |
| Feature selection to enhance a two-stage evolutionary algorithm in product unit neural networks for complex classification problems. | 9 | 0.62 | 2013 |
| A Kernel for Time Series Classification: Application to Atmospheric Pollutants. | 0 | 0.34 | 2012 |
| Unravelling the yeast cell cycle using the TriGen algorithm | 0 | 0.34 | 2011 |
| Triclustering on temporary microarray data using the TriGen algorithm. | 0 | 0.34 | 2011 |
| On the use of algorithms to discover motifs in DNA sequences. | 0 | 0.34 | 2011 |
| Improving the accuracy of a two-stage algorithm in evolutionary product unit neural networks for classification by means of feature selection | 5 | 0.47 | 2011 |
| Multiobjective simulation optimisation in software project management | 10 | 0.61 | 2011 |
| Revisiting the yeast cell cycle problem with the improved TriGen algorithm | 0 | 0.34 | 2011 |
| Inferring gene-gene associations from Quantitative Association Rules. | 1 | 0.35 | 2011 |
| Mining Quantitative Association Rules In Microarray Data Using Evolutive Algorithms | 0 | 0.34 | 2011 |
| Inferring gene regression networks with model trees. | 23 | 0.98 | 2010 |
| Evolutionary q-Gaussian radial basis functions for improving prediction accuracy of gene classification using feature selection | 0 | 0.34 | 2010 |
| Knowledge representation and applied decision making (KREAM) | 0 | 0.34 | 2010 |
| Using remote data mining on LIDAR and imagery fusion data to develop land cover maps | 0 | 0.34 | 2010 |
| Improving Time Series Forecasting by Discovering Frequent Episodes in Sequences | 2 | 0.41 | 2009 |
| LBF: A Labeled-Based Forecasting Algorithm and Its Application to Electricity Price Time Series | 13 | 1.55 | 2008 |
| Best Agglomerative Ranked Subset for Feature Selection | 13 | 0.77 | 2008 |
| Identificación de Fallos en Módulos Software. | 0 | 0.34 | 2008 |
