Data Analysis and Applications 3 : Computational, Classification, Financial, Statistical and Stochastic Methods (Hardcover, 3 ed)

Part 1. Computational Data Analysis and Methods 1. Semi-supervised Learning Based on Distributionally Robust Optimization, Jose Blanchet and Yang Kang. 2. Updating of PageRank in Evolving Treegraphs, Benard Abola, Pitos Seleka Biganda, Christopher Engstorm, John Magero Mango, Godwin Kakuba and Sergei Silvestrov. 3. Exploring The Relationship Between Ordinary PageRank, Lazy PageRank and Random Walk with Backstep PageRank for Different Graph Structures, Pitos Seleka Biganda, Benard Abola, Christopher Engstorm, John Magero Mango, Godwin Kakuba and Sergei Silvestrov. 4. On the Behavior of Alternative Splitting Criteria for CUB Model-based Trees, Carmela Cappelli, Rosaria Simone and Francesca Di Iorio. 5. Investigation on Life Satisfaction Through (Stratified) Chain Regression Graph Models, Federica Nicolussi and Manuela Cazzaro. Part 2. Classification Data Analysis and Methods 6. Selection of Proximity Measures for a Topological Correspondence Analysis, Rafik Abdelssam. 7. Support Vector Machines: A Review and Applications in Statistical Process Monitoring, Anastasios Apsemidis and Stelios Psarakis. 8. Binary Classification Techniques: An Application on Simulated and Real Bio-medical Data, Fragkiskos G. Bersimis, Iraklis Varlamis, Malvina Vamvakari and Demosthenes B. Panagiotakos. 9. Some Properties of the Multivariate Generalized Hyperbolic Models, Stergios B. Fotopoulos, Venkata K. Jandhyala and Alex Paparas. 10. On Determining the Value of Online Customer Satisfaction Ratings ? A Case-based Appraisal, Jim Freeman. 11. Projection Clustering Unfolding: A New Algorithm for Clustering Individuals or Items in a Preference Matrix, Mariangela Sciandra, Antonio DAmbrosio and Antonella Plaia.