rule-based classifiers
On Applying Sampling Methods and Rule Based Classifiers
... the rule based ...over-sampling. Rule based classifiers such as Conjunctive Rule, Decision Tree with Naive Bayes, De- cision tree, PART and Repeated Incremental Pruning to ...
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Architectures of evolving fuzzy rule based classifiers
... LASSIFICATION is a problem that is well studied and understood. One of the widely referenced texts is [1] where classification is treated in the context of pattern recognition. In [2] classification is considered in the ...
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Using association rules to make rule-based classifiers robust
... Abstract Rule-based classification systems have been widely used in real world applications because of the easy interpretability of ...traditional rule-based classifiers prefer small ...
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Multi-objective evolutionary design of granular rule-based classifiers
... years, rule-based systems have been widely employed in several different application ...of rule-based classifiers, we investigate the importance of determining an effective information ...
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A single-objective and a multi-objective genetic algorithm to generate accurate and interpretable fuzzy rule based classifiers for the analysis of complex financial data
... 50 3 Fuzzy Rule Based Classifiers 3.1 Introduction FLSs discussed in the previous chapter have been used in many application areas, such as control, clustering, regression and classification. This ...
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Evolving Fuzzy Rule-based Classifiers from Data Streams
... offline classifiers, keeping in mind that eClass is designed to work in the more realistic scenario where the data are presented in real time and in significantly greater ...
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Minimal Rule Based Classifiers using PCA on Pima Indians Diabetes Dataset
... care. Rule-based classifier technique has proven its strength in diabetes diagnosis when used the computational ...proposed based on minimum rules which further uses Principal Component Analysis ...
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Applying interval type-2 fuzzy rule based classifiers through a cluster-based class representation
... —Fuzzy Rule-Based Classification Systems (FRBCSs) have the potential to provide so-called interpretable classifiers, ...i.e. classifiers which can be introspective, understood, validated and ...
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Applying interval type 2 fuzzy rule based classifiers through a cluster based class representation
... Abstract—Fuzzy Rule-Based Classification Systems (FRBCSs) have the potential to provide so-called interpretable classifiers, ...i.e. classifiers which can be introspective, understood, ...
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A NOVEL METHODOLOGY FOR CONSTRUCTING RULE-BASED NAÏVE BAYESIAN CLASSIFIERS
... of classifiers have been described in the research ...Example classifiers are decision tree classifiers, rule-based classifiers, and neural networks ...approach ...
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Robust rule-based prediction
... Robust Rule-Based Prediction Jiuyong Li Abstract—This paper studies a problem of robust rule-based classification, ...a rule-based classification model to tolerate missing ...
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Ensemble of Classifiers Based on Association Rule Mining
... Multiple Classifiers Based on Association Rule Mining BCAR, ...multiple classifiers based on association rule ...performed based on a weighted x2 analysis using multiple ...
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Quantile-based classifiers
... Mis- classification rates multiplied by 100 (with standard errors in brackets; all rounded to one digit after the decimal point) for different methods.[r] ...
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Classifiers Evaluation: Comparison of Performance Classifiers Based on Tuples Amount
... performance classifiers to handle the big data including number of tuples and ...between classifiers performance and tuples amount in one dataset ...considered classifiers are Decision Tree, k-NN, ...
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Bayesian classifiers based on kernel density estimation: Flexible classifiers
... The kDB structure allows each predictor X i to have not more than k predictor variables as parents. There are two reasons to restrict the number of parents of a variable with algorithms based on BMNs. Firstly, the ...
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Ontology-based explanation of classifiers
... Our work is focused on the Ontology-Based Data Manage- ment (OBDM) paradigm [6, 11]. Having the layer for linking the data to the ontology is a non trivial extension of the problem, that has important ...
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Compression-based AODE classifiers
... 3 Dip. di Scienze dell’Informazione, Universita’ di Milano The first contribution of this paper is the COMP-AODE classi- fier, which averages over the SPODEs using the compression-based coefficients. We present its ...
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AdaBoost with SVM-based component classifiers
... 6. Conclusions AdaBoost with properly designed SVM-based compo- nent classifiers is proposed in this paper, which is achieved by adaptively adjusting the kernel parameter to get a set of effective RBFSVM component ...
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Automated Attacks on Compression-Based Classifiers
... In principle, random words that, being included in a barely-spam message, make it legitimate, are promoted for future additions; the ones that make a barely-legitimate message spam, are impeded. In the case of passive ...
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Instance selection for model-based classifiers
... these classifiers has an intrinsic bias that stems from assumptions made by the algorithm during its ...that classifiers are still able to take advantage of some of the relationships and structure in the ...
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