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Data science and machine learning = 21st Australasian Conference, AusDM 2023, Auckland, New Zealand, December 11-13, 2023 : proceedings /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Data science and machine learning/ edited by Diana Benavides-Prado ... [et al.].
Reminder of title:	21st Australasian Conference, AusDM 2023, Auckland, New Zealand, December 11-13, 2023 : proceedings /
remainder title:	AusDM 2023
other author:	Benavides-Prado, Diana.
corporate name:	AusDM (Conference)
Published:	Singapore :Springer Nature Singapore : : 2024.,
Description:	xii, 300 p. :ill., digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Data mining - Congresses. -
Online resource:	https://doi.org/10.1007/978-981-99-8696-5
ISBN:	9789819986965

Data science and machine learning = 21st Australasian Conference, AusDM 2023, Auckland, New Zealand, December 11-13, 2023 : proceedings /
Data science and machine learning21st Australasian Conference, AusDM 2023, Auckland, New Zealand, December 11-13, 2023 : proceedings /[electronic resource] :AusDM 2023edited by Diana Benavides-Prado ... [et al.]. - Singapore :Springer Nature Singapore :2024. - xii, 300 p. :ill., digital ;24 cm. - Communications in computer and information science,19431865-0937 ;. - Communications in computer and information science ;1943..

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.

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.

ISBN: 9789819986965

Standard No.: 10.1007/978-981-99-8696-5doiSubjects--Topical Terms:

551626
Data mining
--Congresses.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 006.312

Data science and machine learning = 21st Australasian Conference, AusDM 2023, Auckland, New Zealand, December 11-13, 2023 : proceedings /
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520 $a 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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