Data Analysis, Machine Learning and Knowledge Discovery

• Corporate Author: SpringerLink (Online service)
• Other Authors: Spiliopoulou, Myra (Editor), Schmidt-Thieme, Lars (Editor), Janning, Ruth (Editor)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2014.
• Series: Studies in Classification, Data Analysis, and Knowledge Organization,
• Subjects: Statistics.; Marketing.; Finance.; Data mining.; Biostatistics.; Psychology.; Statistics and Computing/Statistics Programs.; Data Mining and Knowledge Discovery.; Finance, general.; General Psychology.

Data analysis, machine learning and knowledge discovery are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as web and text mining, marketing,...

Table of Contents:

• AREA Statistics and Data Analysis: Classifcation, Cluster Analysis, Factor Analysis and Model Selection
• AREA Machine Learning and Knowledge Discovery: Clustering, Classifiers, Streams and Social Networks
• AREA Data Analysis and Classification in Marketing
• AREA Data Analysis in Finance
• AREA Data Analysis in Biostatistics and Bioinformatics
• AREA Interdisciplinary Domains: Data Analysis in Music, Education and Psychology.- LIS Workshop: Workshop on Classification and Subject Indexing in Library and Information Science.