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Statistical Models and Learning Methods for Complex Data

This book on statistical models and learning methods for complex data comprises a selection of peer-reviewed post-conference papers presented at the 14th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society (CLADAG 2023), held in Salerno, Italy, Septemb...

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Dades bibliogràfiques
Autor corporatiu: SpringerLink (Online service)
Altres autors: Giordano, Giuseppe (Editor), La Rocca, Michele (Editor), Niglio, Marcella (Editor), Restaino, Marialuisa (Editor), Vichi, Maurizio (Editor)
Format: Electrònic eBook
Idioma:anglès
Publicat: Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
Edició:1st ed. 2025.
Col·lecció:Studies in Classification, Data Analysis, and Knowledge Organization,
Matèries:
Mathematical statistics > Data processing.
Statistics .
Data mining.
Quantitative research.
Statistics and Computing.
Statistical Theory and Methods.
Applied Statistics.
Data Mining and Knowledge Discovery.
Data Analysis and Big Data.
Accés en línia:https://doi.org/10.1007/978-3-031-84702-8
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Taula de continguts:
  • - Exploring latent evolving ability in test equating and its effects on final rankings
  • Hidden Markov and related discrete latent variable models An application to compositional data
  • An application of Natural Language Processing Analysis on TripAdvisor Reviews
  • Modelling football players field position via mixture of Gaussians with flexible weights
  • Estimation Issues in Multivariate Panel Data
  • Testing linearity in the single functional index model for dependent data
  • A multi-step approach for streamflow classification
  • Identification of misogynistic accounts on Twitter through Graph Convolutional Networks
  • Topic modeling of publication activity in Hungary and Poland in the fields of economics, finance, and business
  • Circular kernel classification with errors-in-variables
  • Classification Trees Applied to Time Lagged Data to Improve Quality in Official Statistics
  • Trimmed factorial k-means a clustering application to a cookies dataset_Farné and Camillo
  • Visualization of Proximity and Role-based Embeddings in a Regional Labour Flow Network
  • Bridging the Gap Investigating Correlation Clustering and Manifold Learning Connections
  • Improving Performance in Neural Networks by Dendrite-Activated Connection
  • Regression models with compositional regressors in case of structural zeros
  • Multi-Dimensional Robinson Dissimilarities
  • Composite selection criteria for the number of components of a finite mixture for ordinal data
  • Clustering of Italian higher education institutions based on a destination–specific approach
  • Analyzing Italian crime data using matrix-variate hidden Markov models.

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