東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Recent trends and future challenges ...

Davino, Cristina.

FindBook

Google Book

Amazon

博客來

Recent trends and future challenges in learning from data

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Recent trends and future challenges in learning from data/ edited by Cristina Davino ...[et al.].
其他作者:	Davino, Cristina.
出版者:	Cham :Springer Nature Switzerland : : 2024.,
面頁冊數:	x, 153 p. :ill. (some col.), digital ;24 cm.
內容註:	Preface -- Building hierarchies of factors with disjoint factor analysis -- Uncertainty in Latent Trait Models and dimensionality reduction methods for complex data: an analysis of taxpayer perception on the Fiscal System -- The predictivity of access tests for university success -- Asynchronous and synchronous-asynchronous particle swarms -- The impact of the Covid-19 pandemic on modelling volatility and risk analysis of returns in selected European financial markets -- Asymmetric binary regression models for imbalanced datasets: an application to students' churn -- Computational models supporting decision-making in managing publication activity at Polish universities -- Stability of nonparametric methods for cognitive diagnostic assessment -- SMARTS: SeMi-supervised clustering for Assessment of Reviews using Topic and Sentiment -- The equitable and sustainable wellbeing through the pandemic. A first study to assess changes at local level in Italy -- Choice-Based Optimization under High-Dimensional MNL -- A first glance on co-evolution of Boolean networks to simulate the development of cross-talking systems in molecular biology -- Classification on polish fund market during COVID-19 pandemic - extreme risk modeling approach.
Contained By:	Springer Nature eBook
標題:	Data mining - Congresses. -
電子資源:	https://doi.org/10.1007/978-3-031-54468-2
ISBN:	9783031544682

Recent trends and future challenges in learning from data
Recent trends and future challenges in learning from data[electronic resource] /edited by Cristina Davino ...[et al.]. - Cham :Springer Nature Switzerland :2024. - x, 153 p. :ill. (some col.), digital ;24 cm. - Studies in classification, data analysis, and knowledge organization,2198-3321. - Studies in classification, data analysis, and knowledge organization..

Preface -- Building hierarchies of factors with disjoint factor analysis -- Uncertainty in Latent Trait Models and dimensionality reduction methods for complex data: an analysis of taxpayer perception on the Fiscal System -- The predictivity of access tests for university success -- Asynchronous and synchronous-asynchronous particle swarms -- The impact of the Covid-19 pandemic on modelling volatility and risk analysis of returns in selected European financial markets -- Asymmetric binary regression models for imbalanced datasets: an application to students' churn -- Computational models supporting decision-making in managing publication activity at Polish universities -- Stability of nonparametric methods for cognitive diagnostic assessment -- SMARTS: SeMi-supervised clustering for Assessment of Reviews using Topic and Sentiment -- The equitable and sustainable wellbeing through the pandemic. A first study to assess changes at local level in Italy -- Choice-Based Optimization under High-Dimensional MNL -- A first glance on co-evolution of Boolean networks to simulate the development of cross-talking systems in molecular biology -- Classification on polish fund market during COVID-19 pandemic - extreme risk modeling approach.

This book collects together selected peer-reviewed contributions presented at the European Conference on Data Analysis, ECDA 2022, held in Naples, Italy, September 14-16, 2022. Highlighting the role of statistics in discovering novel and interesting patterns in the era of big data, it follows the motto of the conference: "Avoiding drowning in the data: recent trends and future challenges in learning from data". The central focus is on multidisciplinary approaches to data analysis, classification, and the interface between computer science, data mining and statistics. Both methodological and applied topics are covered. The former includes supervised and unsupervised techniques with particular emphasis on advances in regression and clustering analysis and constructing composite indicators. The applications are mainly in risk analysis, biology, and education. The volume is organized into four main macro themes: methodological contributions in the social sciences and education, multivariate analysis methods for big data, innovative contributions for applications inspired by biology, and strategies for analyzing complex data in finance.

ISBN: 9783031544682

Standard No.: 10.1007/978-3-031-54468-2doiSubjects--Topical Terms:

551626
Data mining
--Congresses.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 006.312

Recent trends and future challenges in learning from data
LDR:03538nmm a22003495a 4500 001 2388439
003 DE-He213
005 20240809130244.0
006 m d
007 cr nn 008maaau
008 250916s2024 sz s 0 eng d
020 $a 9783031544682 $q (electronic bk.)
020 $a 9783031544675 $q (paper)
024 7 $a 10.1007/978-3-031-54468-2 $2 doi
035 $a 978-3-031-54468-2
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.D343
072 7 $a UN $2 bicssc
072 7 $a COM021000 $2 bisacsh
072 7 $a UN $2 thema
082 0 4 $a 006.312 $2 23
090 $a QA76.9.D343 $b R295 2024
245 0 0 $a Recent trends and future challenges in learning from data $h [electronic resource] / $c edited by Cristina Davino ...[et al.].
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2024.
300 $a x, 153 p. : $b ill. (some col.), digital ; $c 24 cm.
347 $a text file $b PDF $2 rda
490 1 $a Studies in classification, data analysis, and knowledge organization, $x 2198-3321
505 0 $a Preface -- Building hierarchies of factors with disjoint factor analysis -- Uncertainty in Latent Trait Models and dimensionality reduction methods for complex data: an analysis of taxpayer perception on the Fiscal System -- The predictivity of access tests for university success -- Asynchronous and synchronous-asynchronous particle swarms -- The impact of the Covid-19 pandemic on modelling volatility and risk analysis of returns in selected European financial markets -- Asymmetric binary regression models for imbalanced datasets: an application to students' churn -- Computational models supporting decision-making in managing publication activity at Polish universities -- Stability of nonparametric methods for cognitive diagnostic assessment -- SMARTS: SeMi-supervised clustering for Assessment of Reviews using Topic and Sentiment -- The equitable and sustainable wellbeing through the pandemic. A first study to assess changes at local level in Italy -- Choice-Based Optimization under High-Dimensional MNL -- A first glance on co-evolution of Boolean networks to simulate the development of cross-talking systems in molecular biology -- Classification on polish fund market during COVID-19 pandemic - extreme risk modeling approach.
520 $a This book collects together selected peer-reviewed contributions presented at the European Conference on Data Analysis, ECDA 2022, held in Naples, Italy, September 14-16, 2022. Highlighting the role of statistics in discovering novel and interesting patterns in the era of big data, it follows the motto of the conference: "Avoiding drowning in the data: recent trends and future challenges in learning from data". The central focus is on multidisciplinary approaches to data analysis, classification, and the interface between computer science, data mining and statistics. Both methodological and applied topics are covered. The former includes supervised and unsupervised techniques with particular emphasis on advances in regression and clustering analysis and constructing composite indicators. The applications are mainly in risk analysis, biology, and education. The volume is organized into four main macro themes: methodological contributions in the social sciences and education, multivariate analysis methods for big data, innovative contributions for applications inspired by biology, and strategies for analyzing complex data in finance.
650 0 $a Data mining $v Congresses. $3 551626
650 0 $a Big data $v Congresses. $3 3166510
650 1 4 $a Data Analysis and Big Data. $3 3538537
650 2 4 $a Data Mining and Knowledge Discovery. $3 898250
650 2 4 $a Statistics and Computing. $3 3594429
650 2 4 $a Statistical Theory and Methods. $3 891074
650 2 4 $a Applied Statistics. $3 3300946
650 2 4 $a Statistical Learning. $3 3597795
700 1 $a Davino, Cristina. $3 2148152
710 2 $a SpringerLink (Online service) $3 836513
711 2 $a European Conference on Data Analysis $d (2022 : $c Naples, Italy) $3 3753526
773 0 $t Springer Nature eBook
830 0 $a Studies in classification, data analysis, and knowledge organization. $3 1568262
856 4 0 $u https://doi.org/10.1007/978-3-031-54468-2
950 $a Mathematics and Statistics (SpringerNature-11649)