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Multivariate Discretization for Set Mining
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Relative Unsupervised Discretization for Association Rule Mining
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Technical note: Bias and the quantification of stability
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Supervised and Unsupervised Discretization of Continuous Features
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General and Efficient Multisplitting of Numerical Attributes
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A review of: “Practical Nonpararnetric Statistics. By W. J. CONOVER. (New York: Wiley, 1971.) [Pl" x+462.] £5·25.
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Mining optimized support rules for numeric attributes
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Chi2: feature selection and discretization of numeric attributes
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A Branch and Bound Algorithm for Feature Subset Selection
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Mining quantitative association rules in large relational tables
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Mining optimized association rules for numeric attributes
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Association rules over interval data
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Efficiently mining long patterns from databases
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Mining optimized gain rules for numeric attributes
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Detecting change in categorical data
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Multivariate Generalizations of the Wald-Wolfowitz and Smirnov Two-Sample Tests
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OPUS: An Efficient Admissible Algorithm for Unordered Search
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What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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