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Trends and Applications in Knowledge Discovery and Data Mining: PAKDD 2017 Workshops, MLSDA, BDM, DM


Trends and Applications in Knowledge Discovery and Data Mining: PAKDD 2017 Workshops, MLSDA, BDM, DM
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Beschreibung

Early Classification of Multivariate Time Series on Distributed and In-Memory Platforms.- Behavior Classification of Dairy Cows fitted with GPS collars.- Dynamic Real-time Segmentation and Recongnition of Activities using a Multi-feature Windowing Approach.- Feature Extraction from EEG data for a P300 Based Brain-computer Interface.- Thermal Stratification Prediction at Lake Trevallyn.- Development of a Software Vulnerability Prediction Web Service based on Artificial Neural Networks .- Diversification Heuristics in Bees Swarm Optimization for Association Rules Mining.- Improved CFDP Algorithms Based on Shared Nearest Neighbors and Transitive Closure.- CNN-based Sequence Labeling for Fine-grained Opinion Mining of Microblogs.- A Genetic Algorithm for Interpretable Model Extraction from Decision Tree Ensembles.- Self-Adaptive Weighted Extreme Learning Machine for Imbalanced Classification Problems.- Estimating Word Probabilities with Neural Networks in Latent Dirichlet Allocation.- GA-Apriori: Combining Apriori Heuristic and Genetic Algorithms for Solving the Frequent Itemsets Mining Problem.- Shelf Time Analysis in CTP Insurance Claims Processing.- Automated Product-Attribute Mapping.- A Novel Extreme Learning Machine-based Classification Algorithm for Uncertain Data.- SPGLAD: A Self-Paced Learning-based Crowdsourcing Classification Model.

Eigenschaften

Breite: 157
Gewicht: 342 g
Höhe: 235
Länge: 10
Seiten: 203
Sprachen: Englisch
Autor: Ee-peng Lim, Jeffrey Xu Yu, U Kang, Yang-Sae Moon

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