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Titlebook: Machine Learning and Data Mining in Pattern Recognition; 8th International Co Petra Perner Conference proceedings 2012 Springer-Verlag Berl

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Reduction of Distance Computations in Selection of Pivot Elements for Balanced GHT Structureartitioning depends on the selection of the appropriate set of pivot elements. In the paper, some methods are presented to improve the quality of the partitioning in GHT structure from the viewpoint of balancing factor. The main goal of the investigation is to determine the conditions when costs of
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Hot Deck Methods for Imputing Missing Dataimple yet effective imputation methods are the hot deck procedures. Hot deck methods impute missing values within a data matrix by using available values from the same matrix. The object, from which these available values are taken for imputation within another, is called the donor. The replication
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BINER search based regression algorithm having the advantage of low computational complexity. These desirable features make BINER a very attractive alternative to existing approaches. The algorithm is interesting because instead of directly predicting the value of response variable, it recursively narrow
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A New Approach for Association Rule Mining and Bi-clustering Using Formal Concept Analysisics. However, to our knowledge, no algorithm was introduced for performing these two tasks in one process. We propose a new approach called FIST for extracting bases of extended association rules and conceptual bi-clusters conjointly. This approach is based on the frequent closed itemsets framework
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Selecting Classification Algorithms with Active Testingd to analyze a new dataset becomes an ever more challenging task. This is because in many cases . all possibly useful alternatives quickly becomes prohibitively expensive. In this paper we propose a novel technique, called ., that intelligently selects the most useful cross-validation tests. It proc
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Unsupervised Grammar Inference Using the Minimum Description Length Principle engineering where there is a need for describing the syntactic structures of programs. Grammar inference (GI) is the induction of CFGs from sample programs and is a challenging problem. We describe an unsupervised GI approach which uses simplicity as the criterion for directing the inference proces
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How Many Trees in a Random Forest? and real-world applications in diverse domains. However, the associated literature provides almost no directions about how many trees should be used to compose a Random Forest. The research reported here analyzes whether there is an optimal number of trees within a Random Forest, i.e., a threshold
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