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Mining Hierarchical Decision Rules from Hybrid Data with Categorical and Continuous Valued Attributes
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作者 MIAO Duo-qian QIAN Jin +1 位作者 LI Wen ZHANG Ze-hua 《浙江海洋学院学报(自然科学版)》 CAS 2010年第5期420-427,共8页
Decision rules mining is an important issue in machine learning and data mining.However,most proposed algorithms mine categorical data at single level,and these rules are not easily understandable and really useful fo... Decision rules mining is an important issue in machine learning and data mining.However,most proposed algorithms mine categorical data at single level,and these rules are not easily understandable and really useful for users.Thus,a new approach to hierarchical decision rules mining is provided in this paper,in which similarity direction measure is introduced to deal with hybrid data.This approach can mine hierarchical decision rules by adjusting similarity measure parameters and the level of concept hierarchy trees. 展开更多
关键词 Similarity relation Attribute reduction Hierarchical decision rules Hybrid data
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Entanglement dynamics of a Heisenberg chain with Dzyaloshinskii-Moriya interaction
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作者 郑强 张小平 +1 位作者 支启军 任中洲 《Chinese Physics B》 SCIE EI CAS CSCD 2009年第8期3210-3214,共5页
This paper investigates the entanglement dynamics of the system, composed of two qubits A and B with Heisenberg XX spin interactation. There is a third controller qubit C, which only has Dzyaloshinskii-Moriya (DM) s... This paper investigates the entanglement dynamics of the system, composed of two qubits A and B with Heisenberg XX spin interactation. There is a third controller qubit C, which only has Dzyaloshinskii-Moriya (DM) spin-orbit interaction with the qubit B. It is found that depending on the initial state of the controller qubit C and DM interaction, the entanglement of the system displays amplification and sudden birth effects. These effects indicate that one can control the entanglement of the system, which may be helpful for quantum information processing. 展开更多
关键词 entanglement sudden birth entanglement amplification DM interaction
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