Advances in Intelligent Data Analysis XV

Table of Contents

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   Book Overview
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   Chapter 1 DSCo-NG: A Practical Language Modeling Approach for Time Series Classification
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   Chapter 2 Ranking Accuracy for Logistic-GEE Models
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   Chapter 3 The Morality Machine: Tracking Moral Values in Tweets
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   Chapter 4 A Hybrid Approach for Probabilistic Relational Models Structure Learning
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   Chapter 5 On the Impact of Data Set Size in Transfer Learning Using Deep Neural Networks
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   Chapter 6 Obtaining Shape Descriptors from a Concave Hull-Based Clustering Algorithm
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   Chapter 7 Visual Perception of Discriminative Landmarks in Classified Time Series
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   Chapter 8 Spotting the Diffusion of New Psychoactive Substances over the Internet
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    Chapter 9 Feature Selection Issues in Long-Term Travel Time Prediction
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    Chapter 10 A Mean-Field Variational Bayesian Approach to Detecting Overlapping Communities with Inner Roles Using Poisson Link Generation
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    Chapter 11 Online Semi-supervised Learning for Multi-target Regression in Data Streams Using AMRules
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    Chapter 12 A Toolkit for Analysis of Deep Learning Experiments
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    Chapter 13 The Optimistic Method for Model Estimation
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    Chapter 14 Does Feature Selection Improve Classification? A Large Scale Experiment in OpenML
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    Chapter 15 Learning from the News: Predicting Entity Popularity on Twitter
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    Chapter 16 Multi-scale Kernel PCA and Its Application to Curvelet-Based Feature Extraction for Mammographic Mass Characterization
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    Chapter 17 Weakly-Supervised Symptom Recognition for Rare Diseases in Biomedical Text
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    Chapter 18 Estimating Sequence Similarity from Read Sets for Clustering Sequencing Data
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    Chapter 19 Widened Learning of Bayesian Network Classifiers
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    Chapter 20 Vote Buying Detection via Independent Component Analysis
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    Chapter 21 Unsupervised Relation Extraction in Specialized Corpora Using Sequence Mining
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    Chapter 22 A Framework for Interpolating Scattered Data Using Space-Filling Curves
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    Chapter 23 Privacy-Awareness of Distributed Data Clustering Algorithms Revisited
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    Chapter 24 Bi-stochastic Matrix Approximation Framework for Data Co-clustering
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    Chapter 25 Sequential Cost-Sensitive Feature Acquisition
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    Chapter 26 Explainable and Efficient Link Prediction in Real-World Network Data
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    Chapter 27 DGRMiner: Anomaly Detection and Explanation in Dynamic Graphs
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    Chapter 28 Similarity Based Hierarchical Clustering with an Application to Text Collections
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    Chapter 29 Determining Data Relevance Using Semantic Types and Graphical Interpretation Cues
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    Chapter 30 A First Step Toward Quantifying the Climate’s Information Production over the Last 68,000 Years
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    Chapter 31 HAUCA Curves for the Evaluation of Biomarker Pilot Studies with Small Sample Sizes and Large Numbers of Features
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    Chapter 32 Stability Evaluation of Event Detection Techniques for Twitter
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    Chapter 33 IDA 2016 Industrial Challenge: Using Machine Learning for Predicting Failures
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    Chapter 34 An Optimized k-NN Approach for Classification on Imbalanced Datasets with Missing Data
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    Chapter 35 Combining Boosted Trees with Metafeature Engineering for Predictive Maintenance
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    Chapter 36 Prediction of Failures in the Air Pressure System of Scania Trucks Using a Random Forest and Feature Engineering