Titlebook: Data Analysis, Machine Learning and Knowledge Discovery; Myra Spiliopoulou,Lars Schmidt-Thieme,Ruth Janning Conference proceedings 2014 Sp

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Data Analysis, Machine Learning and Knowledge Discovery

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The Most Dangerous Districts of Dortmundever, can these results be trusted? Following the press office of Dortmund’s police, offences might not be uniformly reported by the districts to the office and small offences like pick-pocketing are never reported in police press reports. Therefore, this case could also be an example how an unsyste

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Visual Models for Categorical Data in Economic Researchsualization techniques for log-linear models. Some graphs, e.g. mosaic display plots are well-suited for detecting patterns of association in the process of model building, others are useful in model diagnosis and graphical presentation and summaries. The use of log-linear analysis, as well as visua

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Predictive Validity of Tracking Decisions: Application of a New Validation Criterionon, we determined two competence levels. With respect to their individual scores, we assigned each student to one of these levels. It turned out that about 21 . of the students attended a track that did not match their competence level. Whereas the agreement between tracking decisions and actual tra

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Support Vector Machines on Large Data Sets: Simple Parallel Approachesime considerably, with only minor loss in accuracy. We compare the Cascade SVM to the standard SVM and a simple parallel bagging method w.r.t. both classification accuracy and training time. We also introduce a new stepwise bagging approach that exploits parallelization in a better way than the Casc

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Dual Scaling Classification and Its Application in Archaeometryh category is transformed into a score. Then a classifier can be derived from the scores simply in an additive manner over all variables. It will be compared with the simple Bayesian classifier (SBC). Examples and applications to archaeometry (provenance studies of Roman ceramics) are presented.

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