Algorithms from and for Nature and Life: Classification and Data Analysis
Berthold Lausen, Dirk Van den Poel, Alfred Ultsch
Springer Science & Business Media, Aug 28, 2013 - Computers - 547 pages
This volume provides approaches and solutions to challenges occurring at the interface of research fields such as, e.g., data analysis, data mining and knowledge discovery, computer science, operations research, and statistics. In addition to theory-oriented contributions various application areas are included. Moreover, traditional classification research directions concerning network data, graphs, and social relationships as well as statistical musicology describe examples for current interest fields tackled by the authors. The book comprises a total of 55 selected papers presented at the Joint Conference of the German Classification Society (GfKl), the German Association for Pattern Recognition (DAGM), and the Symposium of the International Federation of Classification Societies (IFCS) in 2011.
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Part II Clustering and Unsupervised Learning
Part III Statistical Data Analysis Visualization and Scaling
Part IV Bioinformatics and Biostatistics
Part V Archaeology and Geography Psychology and Educational Sciences
Part VI Text Mining Social Networks and Clustering
Part VII Banking and Finance
Part VIII Marketing and Management
Part IX Music Classification Workshop
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algorithm applied approach audio calculated centroid cluster analysis cluster at layer coefficients columns computation configuration copula correlation corresponding covariance Data Analysis data set defined detection dimensional dimensionality reduction distribution estimation Euclidean distance evaluation factors feature extraction function gene graph images International Publishing Switzerland item response models iterations Journal k-means Knowledge Organization latent class Lausen linear LLRA Mahalanobis distance marginal marginal likelihood matrix maximum measure method metric mixture model modularity multidimensional multidimensional scaling multivariate Nehren number of clusters observations obtained optimization outliers PARAMAP parameters partial partition performance portfolio prediction Principal Components Analysis problem procedure proposed Publishing Switzerland 2013 Rand index rankings Rasch model References ROC curve sample Sect segmentation similar simulation solution spectra Springer International Publishing Statistics step structure Studies in Classification Table values variables vector weights window