Anmerkung: Intro -- Preface -- Organization -- Contents -- Bioinformatics -- A Comparison of Machine Learning Techniques for the Detection of Type-4 PhotoParoxysmal Responses in Electroencephalographic Signals -- 1 Introduction -- 2 Preliminaries and Related Work -- 3 Type-4 PPR Detection Using ML -- 3.1 Dimensional Reduction -- 3.2 Clustering and Classification -- 4 Materials and Methods -- 4.1 Data Set Description -- 4.2 Experimentation Design -- 5 Results and Discussion -- 6 Conclusions and Future Work -- References -- Smartwatch Sleep-Tracking Services Precision Evaluation Using Supervised Domain Adaptation -- 1 Introduction -- 2 The Proposal -- 2.1 Step1: RAW Signals Preprocessing -- 2.2 Step2: Features Computing -- 2.3 Steps 3 and 4: Models Training and Domain Adaptation -- 3 Numerical Results -- 3.1 Materials and Methods -- 3.2 Experimentation Set up -- 3.3 Numerical Results -- 4 Conclusions and Future Work -- References -- Tracking and Classification of Features in the Bio-Inspired Layered Networks -- 1 Introduction -- 2 Bio-Inspired Neural Networks -- 2.1 Background of Asymmetric Neural Networks Based on the Bio-Inspired Network -- 2.2 Model of Asymmetric Networks -- 2.3 Tracking in the Asymmetric Networks -- 2.4 Orthogonality in the Asymmetric Layered Networks -- 3 Sparse Coding for Classification in the Extended Asymmetric Networks -- 3.1 Independence and Sparse Coding on the Orthogonal Subnetworks -- 3.2 Generation of Independent Basis Set via Sparse Coding Realization -- 4 Application to Data Classification via Sparse Coding Realization in the Asymmetric Networks -- 5 Conclusion -- References -- Frailty Related Survival Risks at Short and Middle Term of Older Adults Admitted to Hospital -- 1 Introduction -- 2 Materials and Methods -- 2.1 Study Design and Subjects -- 2.2 Statistical Methods -- 3 Results -- 4 Discussion. , 5 Conclusions and Future Work -- References -- On the Analysis of a Real Dataset of COVID-19 Patients in Alava -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Study Design -- 3.2 Ethical Approval and Patient Consent -- 3.3 Data Collection and Description -- 3.4 Attribute Analysis -- 3.5 Principal Component Analysis -- 3.6 Logistic Regression Feature Importance -- 4 Discussion -- 5 Conclusion -- References -- Indoor Access Control System Through Symptomatic Examination Using IoT Technology, Fog Computing and Cloud Computing -- 1 Introduction -- 2 Related Works -- 3 Operation of the Control System -- 3.1 Facial Recognition Module -- 3.2 Steps of the Detection System -- 3.3 Medical Sensors -- 3.4 Fog Computing -- 3.5 Statistics Management and User Registration Module -- 3.6 Accessibility Improvements -- 4 Conclusions and Future Work Lines -- References -- Data Mining and Decision Support Systems -- Measuring the Quality Information of Sources of Cybersecurity by Multi-Criteria Decision Making Techniques -- 1 Introduction -- 2 Background -- 2.1 Related Work -- 2.2 DQ Model -- 3 Ranking of Sources by MCDM -- 3.1 Weighted Sum Model (WSM) -- 3.2 Analytic Hierarchy Process (AHP) -- 3.3 Concordance Between Rankings -- 4 Experimental Section -- 5 Results and Discussion -- 6 Conclusions and Future Work -- References -- A Case of Study with the Clustering R Library to Measure the Quality of Cluster Algorithms -- 1 Introduction -- 2 The Clustering Package -- 3 A Case Study Using the Clustering Library on the Dataset of Deaths -- 4 Graphical Distribution of Results -- 5 Conclusions -- References -- Comparing Clustering Techniques on Brazilian Legal Document Datasets -- 1 Introduction -- 2 Related Work -- 3 Theoretical Basis -- 3.1 Clustering Algorithms -- 3.2 Natural Language Processing Techniques -- 4 Methodology -- 4.1 Models Description. , 4.2 Databases, Preprocessing and Embedding -- 4.3 Clustering Evaluation Framework -- 4.4 Clustering Human Evaluation -- 5 Results and Discussion -- 6 Conclusion -- 7 Future Work -- References -- Improving Short Query Representation in LDA Based Information Retrieval Systems -- 1 Introduction -- 2 Material and Methods -- 2.1 Information Retrieval Systems -- 2.2 Latent Dirichlet Allocation -- 2.3 Relevance Estimation -- 3 Proposed Query Representation Method: LDAW -- 3.1 LDAW Calculation Method -- 3.2 Relevance of the Word in Each LDA Topic -- 3.3 Relevance of the Word in the Corpus Vocabulary -- 3.4 Relevance of the Word in the Query -- 3.5 Word Vector Calculation -- 4 Evaluation -- 4.1 Data Sets -- 4.2 Evaluation Measures -- 4.3 Text Pre-processing -- 4.4 Experiments Description -- 5 Results and Discussion -- 6 Conclusions -- References -- A New Game Theoretic Based Random Forest for Binary Classification -- 1 Introduction -- 2 Decision Trees and Random Forests -- 2.1 FROG -- 2.2 RF-FROG -- 3 Numerical Experiments -- 4 Conclusions -- References -- Concept Drift Detection to Improve Time Series Forecasting of Wind Energy Generation -- 1 Introduction -- 2 Materials and Method -- 2.1 Dataset -- 2.2 Concept Drifts Detection Techniques -- 2.3 Comparison Procedure -- 3 Results -- 4 Conclusions -- References -- A Decision Support Tool for the Static Allocation of Emergency Vehicles to Stations -- 1 Introduction -- 2 Background -- 3 Architecture -- 4 Static Ambulance Allocation Model -- 4.1 Problem Description -- 4.2 Mathematical Model -- 5 Evaluation -- 5.1 Computational Evaluation -- 5.2 Model Evaluation -- 6 Conclusions -- References -- Adapting K-Means Algorithm for Pair-Wise Constrained Clustering of Imbalanced Data Streams -- 1 Introduction -- 2 Algorithm -- 3 Experiments -- 3.1 Research Protocol -- 3.2 Experimental Setup -- 3.3 Results. , 4 Conclusions -- References -- Small Wind Turbine Power Forecasting Using Long Short-Term Memory Networks for Energy Management Systems -- 1 Introduction -- 2 Case Study -- 2.1 Sotavento Galicia Building -- 2.2 Dataset Description -- 3 Energy Management System -- 4 Experiments and Results -- 4.1 Experiments Setup -- 4.2 Results -- 5 Conclusions and Future Work -- References -- CORE-BCD-mAI: A Composite Framework for Representing, Querying, and Analyzing Big Clinical Data by Means of Multidimensional AI Tools -- 1 Introduction -- 2 Motivations: Combining Multidimensional AI Tools and Big Clinical Data -- 3 CORE-BCD-mAI: Methodologies and Anatomy -- 4 CORE-BCD-mAI: Research Challenges -- 5 Conclusions and Future Work -- References -- Generalized Fisher Kernel with Bregman Divergence -- 1 Introduction -- 2 Statement of the Problem -- 2.1 Non-parametric Approach -- 3 Non Parametric General Solutions -- 4 Examples -- 5 Conclusion -- References -- A HAIS Approach to Predict the Energy Produced by a Solar Panel -- 1 Introduction -- 2 Case of Study -- 2.1 Sotavento Bioclimatic House -- 2.2 Bioclimatic House Facilities -- 2.3 Solar Thermal System -- 3 Techniques Applied -- 3.1 Statistical Regression Techniques -- 3.2 Artificial Neural Networks -- 3.3 Clustering Technique -- 4 Results and Discussion -- 5 Conclusions and Future Work -- References -- Deep Learning -- Companion Losses for Ordinal Regression -- 1 Introduction -- 2 OR Overview -- 3 Companion Losses for OR -- 4 Experimental Results -- 4.1 Companion Loss Models -- 4.2 Comparison with Classical or Models -- 5 Discussion and Conclusions -- References -- Convex Multi-Task Learning with Neural Networks -- 1 Introduction -- 2 Multi-Task Learning Approaches -- 2.1 Multi-Task Learning with a Feature-Learning Approach -- 2.2 Multi-Task Learning with a Regularization-Based Approach. , 2.3 Multi-Task Learning with a Combination Approach -- 3 Convex MTL Neural Networks -- 3.1 Definition -- 3.2 Training Procedure -- 3.3 Implementation Details -- 4 Experimental Results -- 4.1 Problems Description -- 4.2 Experimental Procedure -- 4.3 Analysis of the Results -- 5 Conclusions and Further Work -- References -- Smash: A Compression Benchmark with AI Datasets from Remote GPU Virtualization Systems -- 1 Introduction -- 2 Related Work -- 2.1 Remote GPU Virtualization -- 2.2 Compression Libraries -- 2.3 Datasets Used with Compression Libraries -- 3 The Smash Compression Benchmark for AI -- 3.1 A New Dataset for AI Applications -- 3.2 The Smash Compression Benchmark -- 4 Experiments -- 5 Conclusion -- References -- Time Series Forecasting Using Artificial Neural Networks -- 1 Introduction -- 2 Background -- 3 Materials and Methods -- 4 ANN Architectures -- 4.1 Multi-layer Neural Network -- 4.2 Recurrent Neural Networks -- 5 Results and Discussion -- 5.1 Recurrent Neural Network Performance -- 5.2 Results Comparison -- 6 Conclusions -- References -- A Fine-Grained Study of Interpretability of Convolutional Neural Networks for Text Classification -- 1 Introduction -- 2 Related Work -- 2.1 Network Interpretability -- 3 Methodology -- 4 Evaluation -- 4.1 Corpora -- 4.2 Model Studied -- 4.3 Experimental Phase -- 4.4 Study of the Interpretability of the Convolutional Layers -- 5 Conclusions and Future Work -- References -- Olive Phenology Forecasting Using Information Fusion-Based Imbalanced Preprocessing and Automated Deep Learning -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Data Preparation -- 3.2 Imbalanced Techniques -- 3.3 Automated Deep Learning Proposal -- 3.4 Benchmark Algorithms -- 4 Experimentation and Results -- 4.1 Dataset -- 4.2 Evaluation Metrics -- 4.3 Experimental Settings -- 4.4 Results and Discussion. , 5 Conclusions.

Anmerkung: Intro -- Preface -- Organization -- Contents -- Data Mining and Knowledge Discovery -- Screening a Case Base for Stroke Disease Detection -- Abstract -- 1 Introduction -- 2 Knowledge Representation and Reasoning -- 3 A Case Study -- 4 Case Based Reasoning -- 5 Conclusions -- Acknowledgments -- References -- SemSynX: Flexible Similarity Analysis of XML Data via Semantic and Syntactic Heterogeneity/Homogeneity Detection -- 1 Introduction -- 1.1 On the Innovativeness of the SemSynX Proposal -- 2 Running Example -- 3 The SemSynX Approach -- 3.1 XML Data Similarity Analysis in SemSynX -- 4 Experimental Results -- 5 Conclusions and Future Work -- References -- Towards Automatic Composition of Multicomponent Predictive Systems -- 1 Introduction -- 2 Related Work -- 3 MCPS Description -- 4 Contribution to Auto-WEKA -- 5 Methodology -- 6 Results and Discussion -- 7 Conclusion and Future Work -- References -- LiCord: Language Independent Content Word Finder -- 1 Introduction -- 2 Related Work -- 3 LiCord: Proposed Framework -- 3.1 NGram Constructor -- 3.2 Function Word Decider -- 3.3 Feature Value Calculator -- 3.4 Classifier Learner -- 4 Experiment -- 4.1 Experiment 1 -- 4.2 Experiment 2 -- 5 Conclusion -- References -- Mining Correlated High-Utility Itemsets Using the Bond Measure -- 1 Introduction -- 2 Preliminaries and Related Work -- 3 The FCHM Algorithm -- 4 Experimental Study -- 5 Conclusion -- References -- An HMM-Based Multi-view Co-training Framework for Single-View Text Corpora -- 1 Introduction -- 2 View Generation -- 3 Co-training with HMM View -- 4 Experiments -- 5 Results -- 6 Conclusions -- References -- Does Sentiment Analysis Help in Bayesian Spam Filtering? -- 1 Introduction -- 2 Related Work -- 2.1 Spam Filtering Techniques -- 2.2 Sentiment Analysis -- 3 Improving Spam Filtering Using Sentiment Analysis -- 3.1 Bayesian Spam Filtering. , 3.2 Sentiment Analysis -- 4 Experimental Results -- 4.1 Bayesian Spam Filtering Experiment -- 4.2 Sentiment Analysis -- 5 Conclusions -- References -- A Context-Aware Keyboard Generator for Smartphone Using Random Forest and Rule-Based System -- Abstract -- 1 Introduction -- 2 Related Works -- 3 Adaptive Keyboard Generator -- 3.1 Data Collection -- 3.2 Data Analysis -- 3.3 User Behavior Pattern Recognition -- 3.4 GUI Generation -- 4 Experimental Results -- 5 Concluding Remarks -- Acknowledgements -- References -- Privacy Preserving Data Mining for Deliberative Consultations -- 1 Introduction -- 2 Privacy Preserving Data Mining for Deliberative Consultations - Literature Review -- 2.1 Levels of Privacy Preserving -- 2.2 Types of Data Partitioning in Privacy Preserving Data Mining -- 2.3 Methods of Data Modification in Privacy Preserving Data Mining -- 2.4 Privacy Preserving Techniques -- 3 Usability of Privacy Preserving Techniques in Deliberative Consultations -- 4 Conclusions and Future Work -- References -- Feature Selection Using Approximate Multivariate Markov Blankets -- 1 Introduction -- 2 Theoretical Foundations -- 2.1 Bivariate Approach for Feature Redundancy -- 2.2 Multivariate Approach -- 3 Data -- 3.1 Synthetic Datasets -- 3.2 UCI Datasets -- 4 Experiments and Results -- 4.1 Synthetic Datasets -- 4.2 UCI Datasets -- 5 Conclusions and Future Works -- References -- Student Performance Prediction Applying Missing Data Imputation in Electrical Engineering Studies Degree -- Abstract -- 1 Introduction -- 2 Case of Study -- 3 The Used Data Imputation Techniques -- 3.1 The MICE Algorithm -- 3.2 The AAA Algorithm -- 3.3 Models Validation -- 4 Results -- 5 Conclusions -- Acknowledgments -- References -- Accuracy Increase on Evolving Product Unit Neural Networks via Feature Subset Selection -- 1 Introduction -- 2 Methodology. , 2.1 Product Unit Neural Networks and Training Procedure -- 2.2 Experimental Design Distribution -- 2.3 Feature Selection -- 3 Proposal Description -- 4 Experimentation -- 5 Results -- 5.1 Results Applying EDD and EDDFS -- 5.2 Results Obtained with State-of-the-art Classifiers -- 6 Conclusions -- References -- Time Series -- Rainfall Prediction: A Deep Learning Approach -- 1 Introduction -- 2 Related Work -- 3 Data Preparation -- 4 Proposed Architecture -- 5 Experiments -- 5.1 Optimizing the Proposed Network Architecture -- 5.2 Evaluation of the Proposed Network -- 6 Conclusions and Future Work -- References -- Time Series Representation by a Novel Hybrid Segmentation Algorithm -- 1 Introduction -- 2 Hybrid Segmentation Algorithm -- 2.1 Summary of the Algorithm -- 2.2 Genetic Algorithm -- 2.3 Local Search -- 3 Experimental Results and Discussion -- 3.1 Time Series Analysed -- 3.2 Experimental Setting -- 3.3 Discussion -- 4 Conclusions -- References -- A Nearest Neighbours-Based Algorithm for Big Time Series Data Forecasting -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Time Series Forecasting Based on Nearest Neighbours -- 3.2 Algorithm Implementation for Apache Spark -- 4 Results -- 4.1 Datasets Description -- 4.2 Design of Experiments -- 4.3 Electricity Consumption Big Data Time Series Forecasting -- 5 Conclusions -- References -- Active Learning Classifier for Streaming Data -- 1 Introduction and Related Works -- 2 Active Learning Classifier for Data Stream -- 3 Experiments -- 3.1 Goals -- 3.2 Results -- 3.3 Discussion -- 4 Conclusions -- References -- Bio-inspired Models and Evolutionary Computation -- Application of Genetic Algorithms and Heuristic Techniques for the Identification and Classification of the Information Used by a Recipe Recommender -- 1 Introduction -- 2 Specification of the Proposed Genetic Algorithm. , 2.1 Codification -- 2.2 Starting Generation -- 2.3 GA Operators -- 2.4 Fitness Function -- 2.5 Getting the New Generation -- 2.6 Results -- 3 Heuristics -- 4 Conclusions -- References -- A New Visualization Tool in Many-Objective Optimization Problems -- 1 Introduction -- 2 Related Work -- 3 Proposed Tool -- 3.1 Overview Step -- 3.2 Detail Step -- 4 Experimental Results -- 5 Conclusion -- References -- A Novel Adaptive Genetic Algorithm for Mobility Management in Cellular Networks -- 1 Introduction -- 2 Basic Concepts -- 2.1 The Genetic Algorithm -- 2.2 Adaptation Within Evolutionary Algorithms -- 2.3 Studied Adaptation Strategies -- 2.4 Mobility Management in Cellular Networks -- 3 The Proposed Approach -- 3.1 Initialisation -- 3.2 Selection -- 3.3 Reproduction -- 3.4 Evaluation and Replacement -- 4 Experimental Results and Analysis -- 4.1 Numerical Results -- 4.2 Discussion and Interpretation -- 5 Conclusions -- References -- Bio-Inspired Algorithms and Preferences for Multi-objective Problems -- 1 Introduction -- 2 Foundations -- 3 Interactive Algorithms -- 3.1 CI-NSGA-II -- 3.2 CI-SMS-EMOA -- 3.3 CI-SPEA2 -- 4 Performance Indicators -- 4.1 Referential Cluster Variance Indicator -- 4.2 Hull Volume Indicator -- 5 Experimental Results -- 6 Final Remarks -- References -- Assessment of Multi-Objective Optimization Algorithms for Parametric Identification of a Li-Ion Battery Model -- 1 Introduction -- 2 Semi-physical Model for Li-Ion Battery -- 3 Multi-Objective Approach for Semi-physical Models -- 4 Experimental Results -- 4.1 Experimental Setup and Electronic Instrumentation -- 4.2 Statistical Experimental Design -- 4.3 Numerical Results and Discussion -- 5 Conclusion -- References -- Comparing ACO Approaches in Epilepsy Seizures -- 1 Introduction -- 2 FRBC Learning Metaheuristics for ECI -- 2.1 Pittsburg Learning of Generalized FRBC Models. , 2.2 Ant-Miner+ for Learning FRBCs with Michigan Style -- 3 Experimentation and Results -- 3.1 Materials and Methods -- 3.2 Evaluating the Effect of the Partitioning in the ACO Pittsburg Learning and Ant-Miner+ Michigan Approach -- 4 Conclusions and Future Work -- References -- Estimating the Maximum Power Delivered by Concentrating Photovoltaics Technology Through Atmospheric Conditions Using a Differential Evolution Approach -- 1 Introduction -- 2 CPV Technology -- 2.1 Study of Influential Atmospheric Conditions on the Electric Performance of CPV Modules -- 2.2 The Use of SMR and APE Indexes to Characterise the DNI Spectral Distribution -- 3 Experimental Study -- 4 Conclusions -- References -- A Hybrid Bio-inspired ELECTRE Approach for Decision Making in Purchasing Agricultural Equipment -- Abstract -- 1 Introduction -- 2 Agricultural Decision Making and Related Work -- 3 A Hybrid Bio-Inspired ELECTRE Model -- 3.1 Multiple Criteria Decision Making ELECTRE I Model -- 3.2 Application of Bio-Inspired Ranking Method -- 4 Choosing and Decision Making for Agricultural Equipment -- 4.1 Data Collection - Combine Harvester -- 5 Experimental Results -- 5.1 Experimental Results - Combine Harvester -- 5.2 Complete Ranking PROMETHEE II Method - Experimental Results -- 5.3 Discussion on Experimental Results -- 5.4 Experimental Results - Purchasing Irrigation Equipment -- 6 Conclusion and Future Work -- Acknowledgments -- References -- Learning Algorithms -- Evaluating the Difficulty of Instances of the Travelling Salesman Problem in the Nearby of the Optimal Solution Based on Random Walk Exploration -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Travelling Salesman Problem and Instances -- 3.2 Experimental Setup -- 4 Analysis -- 4.1 How Far from the Optimal Fitness? -- 4.2 Area as Metric -- 4.3 Comparison with the Phase Transition Parameter for TSP. , 5 Conclusions and Future Work.