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A Decision Tree Algorithm Based on Rough Set Theory after Dimensionality Reduction [PDF]
International Journal of Computer Applications, 2011 Decision tree technology has proven to be a valuable way of capturing human decision making within a computer. As ID3 select those attribute as splitting attributes which have different values whether it classify dataset properly or not. There is another drawback of ID3 which repeat sub tree many times and select same attribute many times.
Shailendra Kumar Shrivastava +1 more
semanticscholar +3 more sources
Knowledge Discovery in Distance Relay Event Report: A Comparative Data-Mining Strategy of Rough Set Theory With Decision Tree [PDF]
IEEE Transactions on Power Delivery, 2010 A protective relay performance analysis is only feasible when the hypothesis of expected relay operation characteristics as decision rules is established as the knowledge base. This has been meticulously accomplished by soliciting the relay knowledge domain from protection experts who are usually constrained by their experience and expertise.
Mohammad Lutfi Othman +4 more
semanticscholar +4 more sources
Meta-Tree Random Forest: Probabilistic Data-Generative Model and Bayes Optimal Prediction
Entropy, 2021 This paper deals with a prediction problem of a new targeting variable corresponding to a new explanatory variable given a training dataset. To predict the targeting variable, we consider a model tree, which is used to represent a conditional ...
Nao Dobashi +3 more
doaj +2 more sources
Granulation using Clustering and Rough Set Theory and its Tree Representation [PDF]
, 2007 Granular computing deals with representation of information in the form of some aggregates and related methods for transformation and analysis for problem solving. A granulation scheme based on clustering and Rough Set Theory is presented with focus on structured conceptualization of information has been presented in this paper.
Girish Kumar Singh, Sonajharia Minz
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Quantification of Temporal Fault Trees Based on Fuzzy Set Theory [PDF]
International Conference on Dependability of Computer Systems, 2014 Fault tree analysis (FTA) has been modified in different ways to make it capable of performing quantitative and qualitative safety analysis with temporal gates, thereby overcoming its limitation in capturing sequential failure behaviour. However, for many systems, it is often very difficult to have exact failure rates of components due to increased ...
Gordon, Neil +3 more
openaire +4 more sources
Decision Tree Construction based on Rough Set Theory under Characteristic Relation [PDF]
Proceedings on Intelligent Systems and Knowledge Engineering (ISKE2007), 2007 Several approaches based on rough set have been proposed for constructing decision tree in complete information systems. In fact, many information systems are incomplete in practical applications. In this paper, a new algorithm, Decision Tree Construction based on Rough Set Theory under Characteristic Relation (DTCRSCR), is proposed for mining ...
Jing Song +3 more
openalex +4 more sources
Data mining of the GAW14 simulated data using rough set theory and tree-based methods [PDF]
BMC Genetics, 2005 Abstract Rough set theory and decision trees are data mining methods used for dealing with vagueness and uncertainty. They have been utilized to unearth hidden patterns in complicated datasets collected for industrial processes. The Genetic Analysis Workshop 14 simulated data were generated using a system that implemented multiple ...
Liang‐Ying Wei +2 more
openalex +5 more sources
Applications of cohomology to set theory II: Todorčević trees
Annals of Pure and Applied Logic, 1996 The author develops a cohomology theory for a class of \(\omega_1\)-trees. This continues the author's investigations in Part I [ibid. 71, 69-106 (1995; Zbl 0824.03029)] on application of cohomology to gaps. An \(\omega_1\)-tree \(T\) is special if there is a function \(f: T\to \mathbb{Z}\) such that if \(s< t\) then \(f(s)\neq f(t)\).
Daniel Eric Talayco
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Constructing Minimal Spanning Tree Based on Rough Set Theory for Gene Selection [PDF]
International Journal of Artificial Intelligence & Applications, 2013 Microarray gene dataset often contains high dimensionalities which cause difficulty in clustering and classification. Datasets containing huge number of genes lead to increased complexity and therefore, degradation of dataset handling performance. Often, all the measured features of these high-dimensional datasets are not relevant for understanding the
Soumen Kumar Pati, Asit Kumar Das
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A Method for Temporal Fault Tree Analysis Using Intuitionistic Fuzzy Set and Expert Elicitation
IEEE Access, 2020 Temporal fault trees (TFTs), an extension of classical Boolean fault trees, can model time-dependent failure behaviour of dynamic systems. The methodologies used for quantitative analysis of TFTs include algebraic solutions, Petri nets (PN), and Bayesian
Sohag Kabir +4 more
doaj +2 more sources