In this paper we proposed new estimators of parameters for a Naive Bayes Classifier based on Beta Distributions. Equations were obtained for these estimators using an EM-like algorithm and they provide numerical estim...
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ISBN:
(纸本)9789814619967
In this paper we proposed new estimators of parameters for a Naive Bayes Classifier based on Beta Distributions. Equations were obtained for these estimators using an EM-like algorithm and they provide numerical estimates for those parameters. Furthermore, two forms for that Naive Bayes Classifier were presented.
We present a new possibilistic mean-variance model using the Fuzzy Laplace distribution (PMVFL). We generated a sequence of results and concluded that results showed an expected behavior of model of possibilistic mean...
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ISBN:
(纸本)9789814619967
We present a new possibilistic mean-variance model using the Fuzzy Laplace distribution (PMVFL). We generated a sequence of results and concluded that results showed an expected behavior of model of possibilistic mean-variance. When we increase the VaR (Value at Risk), in other words, when we consider further loss of market value, we mean that the risk rate will be higher, i.e., larger return rate, higher will be risk rate, this fact has been demonstrated in model.
Multi-follower tri-level (MFTL) decision making addresses compromises among three interacting decision units within a hierarchical system of which multiple followers are involved in two lower-level units. The leader&#...
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ISBN:
(纸本)9789814619967
Multi-follower tri-level (MFTL) decision making addresses compromises among three interacting decision units within a hierarchical system of which multiple followers are involved in two lower-level units. The leader's decision is affected not only by reactions of the followers but also by various relationships among them. The uncooperative relationship is the most basic situation in MFTL decision cases where multiple followers at the same level make individual decisions without any information exchange or share among them. To support such a MFTL decision, this paper firstly proposes a general model for the decision problem and then develops an extreme-point search algorithm based on bi-level Kth-Best approach to solve the model. Finally, a numerical experiment illustrates the decision model and procedures of the extreme-point search algorithm.
In linguistic decision making problems, the set of alternatives are assessed by means of linguistic terms, implying processes of Computing with Words (CWW). The 2-tuple linguistic model provides a computational model ...
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ISBN:
(纸本)9789814619967
In linguistic decision making problems, the set of alternatives are assessed by means of linguistic terms, implying processes of Computing with Words (CWW). The 2-tuple linguistic model provides a computational model that offers linguistic results in the original linguistic domain in a precise way. Furthermore, this model has been extended to carry out processes of CWW in complex decision frameworks. Despite these advantages, this model and its extensions have not been developed in a software tool suite to facilitate the resolution of linguistic decision making problems. In this contribution, we present FLINTSTONES, a fuzzy linguistic decision tools enhancement suite to solve linguistic decision making problems based on the 2-tuple linguistic model and its extensions as well as the FLINTSTONES website.
Within this contribution we establish a theoretical background for studying inverse limits of fuzzy dynamical systems induced by crisp (non-fuzzy) ones. First, we elaborate topological properties of the space of fuzzy...
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ISBN:
(纸本)9789814619967
Within this contribution we establish a theoretical background for studying inverse limits of fuzzy dynamical systems induced by crisp (non-fuzzy) ones. First, we elaborate topological properties of the space of fuzzy sets, such as connectedness and compactness. Second, we focus our attention on dynamical conditions sufficient for the existence of indecomposable continua in the inverse limit space.
In this paper we present a study aimed to define general openings and closing as specific morphological filters.' Specifically, we study how much openings and closing we can be define just by using idempotent dila...
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ISBN:
(纸本)9789814619967
In this paper we present a study aimed to define general openings and closing as specific morphological filters.' Specifically, we study how much openings and closing we can be define just by using idempotent dilations and erosions.
This paper presents an a-resolution method for lattice-valued horn generalized clauses in lattice-valued propositional logic system LP (X) based on lattice implication algebra. In this approach, We give lattice-valued...
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ISBN:
(纸本)9789814619967
This paper presents an a-resolution method for lattice-valued horn generalized clauses in lattice-valued propositional logic system LP (X) based on lattice implication algebra. In this approach, We give lattice-valued horn generalized clause and the correlative concepts in LP(X). The alpha-resolution of two lattice valued horn generalized clauses is also represented in LP(X). It reflects the resolution rules in a resolution process, which aims at deleting cc resolution literals and obtaining a resolvent. This method can provide an efficient tool for automated reasoning in lattice-valued propositional logic system and lattice valued first-order logic system.
Discretization is an important algorithm and considered to be a process of information generalization and data reduction. To avoid information loss and total number of cut point decrease after discretization of contin...
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ISBN:
(纸本)9789814619967
Discretization is an important algorithm and considered to be a process of information generalization and data reduction. To avoid information loss and total number of cut point decrease after discretization of continuous attributes, based on multi-attribute discretization algorithm with good global clustering effects for selecting candidate cut points is proposed. The improved algorithm is combined with the advantages of clustering method and algorithm based on the importance of cut points, The experimental results show that the proposed algorithm can significantly decrease the number of discretization cut points and increase the predictive accuracy of the classifier than both.
This paper presents a feature selection method based on genetic algorithm for unbalanced data. This method improves the fitness function through using the evaluation criterion G-mean for unbalanced data instead of tot...
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ISBN:
(纸本)9789814619967
This paper presents a feature selection method based on genetic algorithm for unbalanced data. This method improves the fitness function through using the evaluation criterion G-mean for unbalanced data instead of total classification accuracy in order to improve the recognition rate of the minor class. Experimental results on several UCI datasets show that the performance of the proposed method outperforms classic genetic algorithm. It not only reduces the feature dimension effectively, but also improves the precision of the minor class.
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