Data Science

Chapter 1 Missing Data Imputation and Its Effect on the Accuracy of Classification

Chapter 2 On Coupling Robust Estimation with Regularization for High-Dimensional Data

Chapter 3 Classification Methods in the Research on the Financial Standing of Construction Enterprises After Bankruptcy in Poland

Chapter 4 On the Identification of Correlated Differential Features for Supervised Classification of High-Dimensional Data

Chapter 5 T-Sharper Images and T-Level Cuts of Fuzzy Partitions

Chapter 6 Benchmarking for Clustering Methods Based on Real Data: A Statistical View

Chapter 7 Representable Hierarchical Clustering Methods for Asymmetric Networks

Chapter 8 A Median-Based Consensus Rule for Distance Exponent Selection in the Framework of Intelligent and Weighted Minkowski Clustering

Chapter 9 Finding Prototypes Through a Two-Step Fuzzy Approach

Chapter 10 Clustering Air Monitoring Stations According to Background and Ambient Pollution Using Hidden Markov Models and Multidimensional Scaling

Chapter 11 Marked Point Processes for Microarray Data Clustering

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

Chapter 13 The Classification and Visualization of Twitter Trending Topics Considering Time Series Variation

Chapter 14 Handling Missing Data in Observational Clinical Studies Concerning Cardiovascular Risk: An Insight into Critical Aspects

Chapter 15 Prediction Error in Distance-Based Generalized Linear Models

Chapter 16 An Inflated Model to Account for Large Heterogeneity in Ordinal Data

Chapter 17 Functional Data Analysis for Optimizing Strategies of Cash-Flow Management

Chapter 18 The Five Factor Model of Personality and Evaluation of Drug Consumption Risk

Chapter 19 Correlation Analysis for Multivariate Functional Data

Chapter 20 Multi-Dimensional Scaling of Sparse Block Diagonal Similarity Matrix

Chapter 21 The Application of Classical and Positional TOPSIS Methods to Assessment Financial Self-sufficiency Levels in Local Government Units

Chapter 22 A Method for Transforming Ordinal Variables

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

Chapter 24 Comparing Partial Least Squares and Partial Possibilistic Regression Path Modeling to Likert-Type Scales: A Simulation Study

Chapter 25 Cause-Related Marketing: A Qualitative and Quantitative Analysis on Pinkwashing

Chapter 26 Predicting the Evolution of a Constrained Network: A Beta Regression Model