Topic
Decision tree model
About: Decision tree model is a research topic. Over the lifetime, 2256 publications have been published within this topic receiving 38142 citations.
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Papers
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TL;DR: The connection between constraints in pattern mining and constraints in decision tree induction is exploited to develop a framework for categorizing decision tree mining constraints, and this framework allows to determine which model constraints can be pushed deeply into the pattern mining process.
Abstract: In this article we show that there is a strong connection between decision tree learning and local pattern mining. This connection allows us to solve the computationally hard problem of finding optimal decision trees in a wide range of applications by post-processing a set of patterns: we use local patterns to construct a global model. We exploit the connection between constraints in pattern mining and constraints in decision tree induction to develop a framework for categorizing decision tree mining constraints. This framework allows us to determine which model constraints can be pushed deeply into the pattern mining process, and allows us to improve the state-of-the-art of optimal decision tree induction.
58 citations
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TL;DR: A novel method is proposed that reduces the computational complexity and realizes an animation in real-time, by means of a boundary condition map expressing space distribution of resistances from tree models automatically.
58 citations
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TL;DR: The model, called Synthetic Tree Model, is a synthesis technique for piecing together, with proper editing, a fault tree from system-independent component information beginnlng with the main failure of interest and proceeding to more basic failures.
Abstract: A model is presented for formulating the Boolean failure logic, cailed the fault tree, for electrical systems from associated schematic diagrams and system-independent component information. The model is developed in detail for electrical systems, while its implication and terminology extend to all fault tree construction. The methodology is verified as formal by fault trees constructed by a computer with typical execution times for a fault tree with 100 gates on the order of 7 sec (on the UNIVAC 1108 computer). The model, called Synthetic Tree Model, is a synthesis technique for piecing together, with proper editing, a fault tree from system-independent component information beginnlng with the main failure of interest and proceeding to more basic failures. The resultant fault trees are in conventional format, use conventional symbols, and are, consequently, immediately compatible with existing solutions techniques. While Synthetic Tree Model develops the fault tree to the level of primary failures, extensions of the model could handle secondary failures, i.e., failure- related feedback between components. ( auth)
58 citations
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TL;DR: A technique for proving min-max norms of sorting algorithms is given and one new algorithm for finding the minimum and maximum elements of a set with fewest comparisons is proved optimal with this technique.
Abstract: A technique for proving min-max norms of sorting algorithms is given. One new algorithm for finding the minimum and maximum elements of a set with fewest comparisons is proved optimal with this technique.
57 citations
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TL;DR: Wang et al. as discussed by the authors used a decision tree approach to determine the key variables to be used for classification and ultimately extract salinized soil from other cover and soil types within the study area.
57 citations