Montanari, Angela

Data Science

Montanari, Angela - Data Science, ebook


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ISBN: 9783319557236
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Table of contents

Part I. Classification Methods for High Dimensional Data

1. Missing Data Imputation and Its Effect on the Accuracy of Classification
Lynette A. Hunt

2. On Coupling Robust Estimation with Regularization for High-Dimensional Data
Jan Kalina, Jaroslav Hlinka

3. Classification Methods in the Research on the Financial Standing of Construction Enterprises After Bankruptcy in Poland
Barbara Pawełek, Krzysztof Gałuszka, Jadwiga Kostrzewska, Maciej Kostrzewski

4. On the Identification of Correlated Differential Features for Supervised Classification of High-Dimensional Data
Shu Kay Ng, Geoffrey J. McLachlan

Part II. Clustering Methods and Applications

5. T-Sharper Images and T-Level Cuts of Fuzzy Partitions
Slavka Bodjanova

6. Benchmarking for Clustering Methods Based on Real Data: A Statistical View
Anne-Laure Boulesteix, Myriam Hatz

7. Representable Hierarchical Clustering Methods for Asymmetric Networks
Gunnar Carlsson, Facundo Mémoli, Alejandro Ribeiro, Santiago Segarra

8. A Median-Based Consensus Rule for Distance Exponent Selection in the Framework of Intelligent and Weighted Minkowski Clustering
Renato Cordeiro Amorim, Nadia Tahiri, Boris Mirkin, Vladimir Makarenkov

9. Finding Prototypes Through a Two-Step Fuzzy Approach
Mario Fordellone, Francesco Palumbo

10. Clustering Air Monitoring Stations According to Background and Ambient Pollution Using Hidden Markov Models and Multidimensional Scaling
Álvaro Gómez-Losada

11. Marked Point Processes for Microarray Data Clustering
Khadidja Henni, Olivier Alata, Abdellatif El Idrissi, Brigitte Vannier, Lynda Zaoui, Ahmed Moussa

12. Social Differentiation of Cultural Taste and Practice in Contemporary Japan: Nonhierarchical Asymmetric Cluster Analysis
Miki Nakai

13. The Classification and Visualization of Twitter Trending Topics Considering Time Series Variation
Atsuho Nakayama

14. Handling Missing Data in Observational Clinical Studies Concerning Cardiovascular Risk: An Insight into Critical Aspects
Nadia Solaro, Daniela Lucini, Massimo Pagani

Part III. Multivariate Methods and Applications

15. Prediction Error in Distance-Based Generalized Linear Models
Eva Boj, Teresa Costa, Josep Fortiana

16. An Inflated Model to Account for Large Heterogeneity in Ordinal Data
Stefania Capecchi, Rosaria Simone, Domenico Piccolo

17. Functional Data Analysis for Optimizing Strategies of Cash-Flow Management
Francesca Salvo, Marcello Chiodi, Pietro Patricola

18. The Five Factor Model of Personality and Evaluation of Drug Consumption Risk
Elaine Fehrman, Awaz K. Muhammad, Evgeny M. Mirkes, Vincent Egan, Alexander N. Gorban

19. Correlation Analysis for Multivariate Functional Data
Tomasz Górecki, Mirosław Krzyśko, Waldemar Wołyński

20. Multi-Dimensional Scaling of Sparse Block Diagonal Similarity Matrix
Tadashi Imaizumi

21. The Application of Classical and Positional TOPSIS Methods to Assessment Financial Self-sufficiency Levels in Local Government Units
Agnieszka Kozera, Aleksandra Łuczak, Feliks Wysocki

22. A Method for Transforming Ordinal Variables
Odysseas Moschidis, Theodore Chadjipadelis

23. Big Data Scaling Through Metric Mapping: Exploiting the Remarkable Simplicity of Very High Dimensional Spaces Using Correspondence Analysis
Fionn Murtagh

24. Comparing Partial Least Squares and Partial Possibilistic Regression Path Modeling to Likert-Type Scales: A Simulation Study
Rosaria Romano, Francesco Palumbo

25. Cause-Related Marketing: A Qualitative and Quantitative Analysis on Pinkwashing
Gabriella Schoier, Patrizia Luca

26. Predicting the Evolution of a Constrained Network: A Beta Regression Model
Luisa Stracqualursi, Patrizia Agati

Keywords: Statistics, Statistical Theory and Methods, Data Mining and Knowledge Discovery, Statistics and Computing/Statistics Programs, Big Data, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences, Statistics for Business/Economics/Mathematical Finance/Insurance

Publication year
Studies in Classification, Data Analysis, and Knowledge Organization
Page amount
16 pages
Natural Sciences
Printed ISBN

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