Supervised and Unsupervised Statistical Data Analysis

The contributions in this book offer new insights into the theoretical and practical challenges of supervised and unsupervised learning, highlighting the remarkable breadth of contemporary statistical research while maintaining methodological rigor. Innovative approaches to statistical modeling, add...

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書誌詳細
団体著者:	SpringerLink (Online service)
その他の著者:	D'Ambrosio, Antonio (編集者), de Rooij, Mark (編集者), De Roover, Kim (編集者), Iorio, Carmela (編集者), La Rocca, Michele (編集者)
フォーマット:	電子媒体 eBook
言語:	英語
出版事項:	Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
版:	1st ed. 2025.
シリーズ:	Studies in Classification, Data Analysis, and Knowledge Organization,
主題:	Machine learning. Statistics . Data mining. Quantitative research. Mathematical statistics > Data processing. Statistical Learning. Statistical Theory and Methods. Data Mining and Knowledge Discovery. Data Analysis and Big Data. Statistics and Computing. Applied Statistics.
オンライン･アクセス:	https://doi.org/10.1007/978-3-032-03042-9
タグ:	タグ追加タグなし, このレコードへの初めてのタグを付けませんか!

目次:

Measuring discrimination in decision making algorithms an approach based on causal inference
Leveraging Social Network Analysis for Semantic Differential Scale: An application to Survey Data
Extending the Boosted Oriented Probabilistic Clustering to the Unit Hypersphere A Textual Data Perspect
Understanding ESG Scores Through Network Analysis A Study Using Graph Neural Networks
Innovative applications of Supervised Learning in addressing missing Data a case study on social surveys
ISP Index A Parsimonious Method to Predict Defaults.

Supervised and Unsupervised Statistical Data Analysis

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