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Data Science and Machine Learning: 21st Australasian Conference, AusDM 2023, Auckland, New Zealand, December 11–13, 2023, Proceedings de Diana Benavides-Prado

Data Science and Machine Learning: 21st Australasian Conference, AusDM 2023, Auckland, New Zealand, December 11–13, 2023, Proceedings: Communications in Computer and Information Science, cartea 1943

Editat de Diana Benavides-Prado, Sarah Erfani, Philippe Fournier-Viger, Yee Ling Boo, Yun Sing Koh
en Limba Engleză Paperback – 5 dec 2023
This book constitutes the proceedings of the 21st Australasian Conference on Data Science and Machine Learning, AusDM 2023, held in Auckland, New Zealand, during December 11–13, 2023.

The 20 full papers presented in this book were carefully reviewed and selected from 50 submissions. The papers are organized in the following topical sections: research track and application track. They deal with topics around data science and machine learning in everyday life. 
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Specificații

ISBN-13: 9789819986958
ISBN-10: 9819986958
Pagini: 300
Ilustrații: XII, 300 p. 94 illus., 83 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.44 kg
Ediția:1st ed. 2024
Editura: Springer Nature Singapore
Colecția Springer
Seria Communications in Computer and Information Science

Locul publicării:Singapore, Singapore

Cuprins

​Research Track: Random Padding Data Augmentation.- Unsupervised Fraud Detection on Sparse Rating Networks.- Semi-Supervised Model-Based Clustering for Ordinal Data.- Damage GAN: A Generative Model for Imbalanced Data.- Text-Conditioned Graph Generation Using Discrete Graph Variational Autoencoders.- Boosting QA Performance through SA-Net and AA-Net with the Read+Verify Framework.- Anomaly Detection Algorithms: Comparative Analysis and Explainability Perspectives.- Towards Fairness and Privacy: A Novel Data Pre-processing Optimization Framework for Non-binary Protected Attributes.- MStoCast: Multimodal Deep Network for Stock Market Forecast..- Few Shot and Transfer Learning with Manifold Distributed Datasets.- Mitigating The Adverse Effects of Long-tailed Data on Deep Learning Models.- Shapley Value Based Feature Selection to Improve Generalization of Genetic Programming for High-Dimensional Symbolic Regression.- Hybrid Models for Predicting Cryptocurrency Price Using Financial and Non-Financial Indicators.- Application Track: Multi-Dimensional Data Visualization for Analyzing Materials.- Law in Order: An Open Legal Citation Network for New Zealand.- Enhancing Resource Allocation in IT Projects: The Potentials of Deep Learning-Based Recommendation Systems and Data-Driven Approaches.- A Comparison of One-Class versus Two-Class Machine Learning Models for Wildfire Prediction in California.- Skin Cancer Detection with Multimodal Data: A Feature Selection Approach Using Genetic Programming.- Comparison of Interpolation Techniques for Prolonged Exposure Estimation: A Case Study on Seven years of Daily Nitrogen Oxide in Greater Sydney.- Detecting Asthma Presentations from Emergency Department Notes:
An Active Learning Approach.