Discovery Science

Table of Contents

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   Book Overview
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   Chapter 1 The CURE for Class Imbalance
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   Chapter 2 Mining a Maximum Weighted Set of Disjoint Submatrices
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   Chapter 3 Dataset Morphing to Analyze the Performance of Collaborative Filtering
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   Chapter 4 Construction of Histogram with Variable Bin-Width Based on Change Point Detection
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   Chapter 5 A Unified Approach to Biclustering Based on Formal Concept Analysis and Interval Pattern Structure
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   Chapter 6 A Sampling-Based Approach for Discovering Subspace Clusters
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   Chapter 7 Epistemic Uncertainty Sampling
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   Chapter 8 Utilizing Hierarchies in Tree-Based Online Structured Output Prediction
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    Chapter 9 On the Trade-Off Between Consistency and Coverage in Multi-label Rule Learning Heuristics
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    Chapter 10 Hyperparameter Importance for Image Classification by Residual Neural Networks
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    Chapter 11 Cellular Traffic Prediction and Classification: A Comparative Evaluation of LSTM and ARIMA
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    Chapter 12 Main Factors Driving the Open Rate of Email Marketing Campaigns
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    Chapter 13 Enhancing BMI-Based Student Clustering by Considering Fitness as Key Attribute
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    Chapter 14 Deep Learning Does Not Generalize Well to Recognizing Cats and Dogs in Chinese Paintings
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    Chapter 15 Temporal Analysis of Adverse Weather Conditions Affecting Wheat Production in Finland
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    Chapter 16 Predicting Thermal Power Consumption of the Mars Express Satellite with Data Stream Mining
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    Chapter 17 Parameter-Less Tensor Co-clustering
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    Chapter 18 Deep Triplet-Driven Semi-supervised Embedding Clustering
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    Chapter 19 Neurodegenerative Disease Data Ontology
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    Chapter 20 Embedding to Reference t-SNE Space Addresses Batch Effects in Single-Cell Classification
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    Chapter 21 Symbolic Graph Embedding Using Frequent Pattern Mining
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    Chapter 22 Feature Selection for Analogy-Based Learning to Rank
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    Chapter 23 Ensemble-Based Feature Ranking for Semi-supervised Classification
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    Chapter 24 Variance-Based Feature Importance in Neural Networks
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    Chapter 25 A Density Estimation Approach for Detecting and Explaining Exceptional Values in Categorical Data
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    Chapter 26 A Framework for Human-Centered Exploration of Complex Event Log Graphs
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    Chapter 27 Sparse Robust Regression for Explaining Classifiers
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    Chapter 28 Efficient Discovery of Expressive Multi-label Rules Using Relaxed Pruning
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    Chapter 29 Evolving Social Networks Analysis via Tensor Decompositions: From Global Event Detection Towards Local Pattern Discovery and Specification
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    Chapter 30 Efficient and Accurate Non-exhaustive Pattern-Based Change Detection in Dynamic Networks
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    Chapter 31 A Combinatorial Multi-Armed Bandit Based Method for Dynamic Consensus Community Detection in Temporal Networks
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    Chapter 32 Resampling-Based Framework for Unbiased Estimator of Node Centrality over Large Complex Network
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    Chapter 33 Layered Learning for Early Anomaly Detection: Predicting Critical Health Episodes
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    Chapter 34 Ensemble Clustering for Novelty Detection in Data Streams
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    Chapter 35 Mining Patterns in Source Code Using Tree Mining Algorithms
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    Chapter 36 KnowBots: Discovering Relevant Patterns in Chatbot Dialogues
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    Chapter 37 Fast Distance-Based Anomaly Detection in Images Using an Inception-Like Autoencoder
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    Chapter 38 Adaptive Long-Term Ensemble Learning from Multiple High-Dimensional Time-Series
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    Chapter 39 Fourier-Based Parametrization of Convolutional Neural Networks for Robust Time Series Forecasting
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    Chapter 40 Integrating LSTMs with Online Density Estimation for the Probabilistic Forecast of Energy Consumption