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Titlebook: Discovery Science; 8th International Co Achim Hoffmann,Hiroshi Motoda,Tobias Scheffer Conference proceedings 2005 Springer-Verlag Berlin He

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樓主: chondrocyte
51#
發(fā)表于 2025-3-30 08:47:22 | 只看該作者
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發(fā)表于 2025-3-30 13:10:36 | 只看該作者
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發(fā)表于 2025-3-30 17:52:39 | 只看該作者
An Experiment with Association Rules and Classification: Post-Bagging and Convictionthis with a particular kind of model: large sets of classification association rules, and in combination with ordinary best rule and weighted voting approaches. We empirically evaluate the effects of the technique in terms of classification accuracy. We also discuss the predictive power of different
54#
發(fā)表于 2025-3-30 21:17:33 | 只看該作者
Movement Analysis of Medaka (,) for an Insecticide Using Decision Tree the insecticide and medaka not treated with the insecticide, diazinon (0.1 mg/l) during a 1 hour period. The observation of behavior through the movement tracking program showed many patterns of the medaka. After much observation, behavioral patterns were divided into four basic patterns: active-sm
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發(fā)表于 2025-3-31 02:57:15 | 只看該作者
Support Vector Inductive Logic Programminggic Programming (ILP). We propose a general method for constructing kernels for Support Vector Inductive Logic Programming (SVILP). The kernel not only captures the semantic and syntactic relational information contained in the data but also provides the flexibility of using arbitrary forms of struc
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發(fā)表于 2025-3-31 08:50:11 | 只看該作者
Measuring Over-Generalization in the Minimal Multiple Generalizations of Biosequencesl multiple generalizations (mmg) for such characterizations. Given any sample set, the mmgs are, roughly speaking, the most (syntactically) specific set of languages containing the sample within a given class of languages. Takae . [17] found the mmgs of the class of pattern languages [1] which inclu
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發(fā)表于 2025-3-31 12:53:37 | 只看該作者
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發(fā)表于 2025-3-31 16:37:39 | 只看該作者
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發(fā)表于 2025-3-31 19:28:13 | 只看該作者
60#
發(fā)表于 2025-3-31 22:03:22 | 只看該作者
https://doi.org/10.1007/978-3-663-19721-8atasets show that our algorithm is able to select a model with the appropriate complexity for the current amount of training data, thus balancing the computational cost of updating a model with the benefits of increasing in accuracy.
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