DFT-ML-Based Property Prediction of Transition Metal Complex Photosensitizers for Photodynamic Therapy. [PDF]
ACS OmegaGao J, Dong Y, Qiu T, Sun W, Du J.
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Exploring Chinese middle-class parents' challenges and coping strategies of dialogic reading in a digital EFL context. [PDF]
Front PsycholZhao L, Cai X, Qin L.
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Bisphosphine ligand conformer selection to enhance descriptor database representation: improving statistical modelling outcomes. [PDF]
Chem SciCadge JA +4 more
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SOME RESULTS IN THE EXTENSION WITH A COHERENT SUSLIN TREE (Aspects of Descriptive Set Theory)
SOME RESULTS IN THE EXTENSION WITH A COHERENT SUSLIN TREE (Aspects of Descriptive Set Theory)openaire
Induction of Decision Trees Based on the Rough Set Theory
, 1998 This paper aimed at two following objectives. One was the introduction of a new measure (R-measure) of dependency between groups of attributes in a data set, inspired by the notion of dependency of attribute in the rough set theory. The second was the application of this measure to the problem of attribute selection in decision tree induction, and an ...
Tu Bao Ho +2 more
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An Algorithm for Decision Tree Construction Based on Rough Set Theory
2008 International Conference on Computer Science and Information Technology, 2008 In this paper, a novel and effective algorithm is introdcued for constructing decision tree. First of all, the knowledge dependence in rough set theory is used to reduce the test attribute set of decision tree, that is, the test attribute space is optimized and hence the attributes which are not correlated with the decision information are deleted ...
Cuiru Wang, Fangfang Ou
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A New Decision Tree Algorithm Based on Rough Set Theory
2009 Asia-Pacific Conference on Information Processing, 2009 Decision tree algorithm has been widely used to classify numeric and categorical attributes. Lots of approaches were suggested in order to induce decision trees. ID3 (Quinlan, 1986), as a heuristic algorithm, is very classic and popular in the induction of decision trees.
Baoshi Ding, Yongqing Zheng, Shaoyu Zang
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The Based on Rough Set Theory Development of Decision Tree after Redundant Dimensional Reduction
2015 Fifth International Conference on Advanced Computing & Communication Technologies, 2015 Decision tree technologists have been examined to be a helpful way to find out the human decision making within a host. Decision tree performs variable screening or feature selection. It requires relatively lesser effort from the users for the preparation of the data.
Priya Pal, Deepak Motwani
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An Optimized Parallel Decision Tree Model Based on Rough Set Theory
, 2008 This paper presents an optimized parallel decision tree model based on rough set theory, first the model divides global database into subsets, then using the intuitive classification ability of decision tree to learn the rules in each subset, at last merge each subset's rule set to obtain the global rule set.
Xiaowang Ye, Zhijing Liu
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