119,623 research outputs found
A proposal on reasoning methods in fuzzy rule-based classification systems
AbstractFuzzy Rule-Based Systems have been succesfully applied to pattern classification problems. In this type of classification systems, the classical Fuzzy Reasoning Method (FRM) classifies a new example with the consequent of the rule with the greatest degree of association. By using this reasoning method, we lose the information provided by the other rules with different linguistic labels which also represent this value in the pattern attribute, although probably to a lesser degree. The aim of this paper is to present new FRMs which allow us to improve the system performance, maintaining its interpretability. The common aspect of the proposals is the participation, in the classification of the new pattern, of the rules that have been fired by such pattern. We formally describe the behaviour of a general reasoning method, analyze six proposals for this general model, and present a method to learn the parameters of these FRMs by means of Genetic Algorithms, adapting the inference mechanism to the set of rules. Finally, to show the increase of the system generalization capability provided by the proposed FRMs, we point out some results obtained by their integration in a fuzzy rule generation process
A proposal on reasoning methods in fuzzy rule-based classification systems
Fuzzy Rule-Based Systems have been succesfully applied to pattern classification problems. In this type of classification systems, the classical Fuzzy Reasoning Method (FRM) classifies a new example with the consequent of the rule with the greatest degree of association. By using this reasoning method, we lose the information provided by the other rules with different linguistic labels which also represent this value in the pattern attribute, although probably to a lesser degree. The aim of this paper is to present new FRMs which allow us to improve the system performance, maintaining its interpretability. The common aspect of the proposals is the participation, in the classification of the new pattern, of the rules that have been fired by such pattern. We formally describe the behaviour of a general reasoning method, analyze six proposals for this general model, and present a method to learn the parameters of these FRMs by means of Genetic Algorithms, adapting the inference mechanism to the set of rules. Finally, to show the increase of the system generalization capability provided by the proposed FRMs, we point out some results obtained by their integration in a fuzzy rule generation process.CICYT TIC96-077
Memory-Based Lexical Acquisition and Processing
Current approaches to computational lexicology in language technology are
knowledge-based (competence-oriented) and try to abstract away from specific
formalisms, domains, and applications. This results in severe complexity,
acquisition and reusability bottlenecks. As an alternative, we propose a
particular performance-oriented approach to Natural Language Processing based
on automatic memory-based learning of linguistic (lexical) tasks. The
consequences of the approach for computational lexicology are discussed, and
the application of the approach on a number of lexical acquisition and
disambiguation tasks in phonology, morphology and syntax is described.Comment: 18 page
A Machine Learning Approach to the Classification of Dialogue Utterances
The purpose of this paper is to present a method for automatic classification
of dialogue utterances and the results of applying that method to a corpus.
Superficial features of a set of training utterances (which we will call cues)
are taken as the basis for finding relevant utterance classes and for
extracting rules for assigning these classes to new utterances. Each cue is
assumed to partially contribute to the communicative function of an utterance.
Instead of relying on subjective judgments for the tasks of finding classes and
rules, we opt for using machine learning techniques to guarantee objectivity.Comment: 12 pages, using nemlap.sty, harvard.sty and agsm.bst, to appear in
Proceedings of NeMLaP-2, Bilkent University, Ankara, Turke
A Bibliography on Fuzzy Automata, Grammars and Lanuages
This bibliography contains references to papers on fuzzy formal languages, the generation of fuzzy languages by means of fuzzy grammars, the recognition of fuzzy languages by fuzzy automata and machines, as well as some applications of fuzzy set theory to syntactic pattern recognition, linguistics and natural language processing
Information Extraction, Data Integration, and Uncertain Data Management: The State of The Art
Information Extraction, data Integration, and uncertain data management are different areas of research that got vast focus in the last two decades. Many researches tackled those areas of research individually. However, information extraction systems should have integrated with data integration methods to make use of the extracted information. Handling uncertainty in extraction and integration process is an important issue to enhance the quality of the data in such integrated systems. This article presents the state of the art of the mentioned areas of research and shows the common grounds and how to integrate information extraction and data integration under uncertainty management cover
An artificial immune system for fuzzy-rule induction in data mining
This work proposes a classification-rule discovery algorithm integrating artificial immune systems and fuzzy systems. The algorithm consists of two parts: a sequential covering procedure and a rule evolution procedure. Each antibody (candidate solution) corresponds to a classification rule. The classification of new examples (antigens) considers not only the fitness of a fuzzy rule based on the entire training set, but also the affinity between the rule and the new example. This affinity must be greater than a threshold in order for the fuzzy rule to be activated, and it is proposed an adaptive procedure for computing this threshold for each rule. This paper reports results for the proposed algorithm in several data sets. Results are analyzed with respect to both predictive accuracy and rule set simplicity, and are compared with C4.5rules, a very popular data mining algorithm
Sellars on Functionalism and Normativity
The term âfunctionalismâ is usually heard in connection with the philosophy of mind or cognition. The functionalism of Wilfrid Sellars, however, is in the first instance as response to the worries about the metaphysics not of mental states, but of meaning. Only late in his career did Sellars explore the possibility of extending his functionalism into an account of cognition. It has been suggested, though, that Sellarsâ extension of his functionalist theory into subpersonal territory is not successful. In particular, there is a worry abroad that in order to be a functionalist about cognitive states, Sellars must succumb to a special form of the Myth of the Given. In this essay I will review and elucidate what I take to be the structure of Sellarsâ functionalism, defending it from this worry. I will suggest a resolution of some apparent textual contradictions based in part on the chronology of Sellarsâ writing, with the assumption that later writings express Sellarsâ more nuanced views.
Draft of 2009
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