For supervised learning, feature selection algorithms attempt to maximise a given function of predictive accuracy. This function usually considers the ability of feature vectors to reflect decision class labels. It is therefore intuitive to retain only those features that are related to or lead to these decision classes. However, in unsupervised learning, decision class labels are not provided, which poses questions such as; which features should be retained? and, why not use all of the information? The problem is that not all features are important. Some of the features may be redundant, and others may be irrelevant and noisy. In this paper, some new fuzzy-rough set-based approaches to unsupervised feature selection are proposed. These approaches require no thresholding or domain information, and result in a significant reduction in dimensionality whilst retaining the semantics of the data.
{"title":"Measures for Unsupervised Fuzzy-Rough Feature Selection","authors":"Neil MacParthaláin, Richard Jensen","doi":"10.3233/HIS-2010-0118","DOIUrl":"https://doi.org/10.3233/HIS-2010-0118","url":null,"abstract":"For supervised learning, feature selection algorithms attempt to maximise a given function of predictive accuracy. This function usually considers the ability of feature vectors to reflect decision class labels. It is therefore intuitive to retain only those features that are related to or lead to these decision classes. However, in unsupervised learning, decision class labels are not provided, which poses questions such as; which features should be retained? and, why not use all of the information? The problem is that not all features are important. Some of the features may be redundant, and others may be irrelevant and noisy. In this paper, some new fuzzy-rough set-based approaches to unsupervised feature selection are proposed. These approaches require no thresholding or domain information, and result in a significant reduction in dimensionality whilst retaining the semantics of the data.","PeriodicalId":330324,"journal":{"name":"2009 Ninth International Conference on Intelligent Systems Design and Applications","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126604246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In cite{porcel09} we presented a fuzzy linguistic recommender system to advise research resources in university digital libraries. The problem of this system is that the user profiles are provided directly by the own users and the process for acquiring user preferences is quite difficult because it requires too much user effort. In this paper we present a new fuzzy linguistic recommender system that facilitates the acquisition of the user preferences to characterize the user profiles. We allow users to provide their preferences by means of an incomplete fuzzy linguistic preference relation. We include tools to manage incomplete information when the users express their preferences, and, in such a way, we show that the acquisition of the user profiles is improved.
{"title":"Using Incomplete Fuzzy Linguistic Preference Relations to Characterize User Profiles in Recommender Systems","authors":"E. Herrera-Viedma, C. Porcel","doi":"10.1109/ISDA.2009.142","DOIUrl":"https://doi.org/10.1109/ISDA.2009.142","url":null,"abstract":"In cite{porcel09} we presented a fuzzy linguistic recommender system to advise research resources in university digital libraries. The problem of this system is that the user profiles are provided directly by the own users and the process for acquiring user preferences is quite difficult because it requires too much user effort. In this paper we present a new fuzzy linguistic recommender system that facilitates the acquisition of the user preferences to characterize the user profiles. We allow users to provide their preferences by means of an incomplete fuzzy linguistic preference relation. We include tools to manage incomplete information when the users express their preferences, and, in such a way, we show that the acquisition of the user profiles is improved.","PeriodicalId":330324,"journal":{"name":"2009 Ninth International Conference on Intelligent Systems Design and Applications","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121512650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. C. Fernández, C. Hervás‐Martínez, F. J. Martínez, Manuel Cruz
This paper proposes a multi-classification pattern algorithm using multilayer perceptron neural network models which try to boost two conflicting main objectives of a classifier, a high correct classification rate and a high classification rate for each class. To solve this machine learning problem, we consider a Memetic Pareto Evolutionary approach based on the NSGA2 algorithm (MPENSGA2), where we defined two objectives for determining the goodness of a classifier: the cross-entropy error function and the variation coefficient of its sensitivities, because both measures are continuous functions, making the convergence more robust. Once the Pareto front is built, we use an automatic selection methodology of individuals: the best model in accuracy (upper extreme in the Pareto front). This methodology is applied to solve six benchmark classification problems, obtaining promising results and achieving a high classification rate in the generalization set with an acceptable level of accuracy for each class.
{"title":"Design of Artificial Neural Networks Using a Memetic Pareto Evolutionary Algorithm Using as Objectives Entropy versus Variation Coefficient","authors":"J. C. Fernández, C. Hervás‐Martínez, F. J. Martínez, Manuel Cruz","doi":"10.1109/ISDA.2009.153","DOIUrl":"https://doi.org/10.1109/ISDA.2009.153","url":null,"abstract":"This paper proposes a multi-classification pattern algorithm using multilayer perceptron neural network models which try to boost two conflicting main objectives of a classifier, a high correct classification rate and a high classification rate for each class. To solve this machine learning problem, we consider a Memetic Pareto Evolutionary approach based on the NSGA2 algorithm (MPENSGA2), where we defined two objectives for determining the goodness of a classifier: the cross-entropy error function and the variation coefficient of its sensitivities, because both measures are continuous functions, making the convergence more robust. Once the Pareto front is built, we use an automatic selection methodology of individuals: the best model in accuracy (upper extreme in the Pareto front). This methodology is applied to solve six benchmark classification problems, obtaining promising results and achieving a high classification rate in the generalization set with an acceptable level of accuracy for each class.","PeriodicalId":330324,"journal":{"name":"2009 Ninth International Conference on Intelligent Systems Design and Applications","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116535999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A multiagent approach to build a decision support system is proposed in this paper. We think the system may be used in different applications types and is appropriate for complex problems as the risk management thanks to a mechanism of perception, representation, characterization and assessment. We focus here on a first level of this approach that intends to re¿ect the dynamic evolution of the current situation. The RoboCupRescue is used as a test bed. Experimentations and results are provided and discussed.
{"title":"Dynamic Representation of a Situation: A Step of a Decision Support Process","authors":"F. Kebair, F. Serin","doi":"10.1109/ISDA.2009.32","DOIUrl":"https://doi.org/10.1109/ISDA.2009.32","url":null,"abstract":"A multiagent approach to build a decision support system is proposed in this paper. We think the system may be used in different applications types and is appropriate for complex problems as the risk management thanks to a mechanism of perception, representation, characterization and assessment. We focus here on a first level of this approach that intends to re¿ect the dynamic evolution of the current situation. The RoboCupRescue is used as a test bed. Experimentations and results are provided and discussed.","PeriodicalId":330324,"journal":{"name":"2009 Ninth International Conference on Intelligent Systems Design and Applications","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116703578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We develop a new approach for dealing with uncertain information in a decision making problem about tourism management. We use a new aggregation operator that uses the uncertain weighted average and the uncertain induced ordered weighted averaging (UIOWA) operator in the same formulation. We study some of the main advantages and properties of the new aggregation called uncertain induced ordered weighted averaging - weighted averaging (UIOWAWA) operator. We study its applicability in a decision making problem about the selection of holiday trips. We see that depending on the particular type of UIOWAWA operator used, the results may lead to different decisions.
{"title":"On the Use of the Uncertain Induced OWA Operator and the Uncertain Weighted Average and its Application in Tourism Management","authors":"J. Merigó, A. M. G. Lafuente, O. Cunill","doi":"10.1109/ISDA.2009.239","DOIUrl":"https://doi.org/10.1109/ISDA.2009.239","url":null,"abstract":"We develop a new approach for dealing with uncertain information in a decision making problem about tourism management. We use a new aggregation operator that uses the uncertain weighted average and the uncertain induced ordered weighted averaging (UIOWA) operator in the same formulation. We study some of the main advantages and properties of the new aggregation called uncertain induced ordered weighted averaging - weighted averaging (UIOWAWA) operator. We study its applicability in a decision making problem about the selection of holiday trips. We see that depending on the particular type of UIOWAWA operator used, the results may lead to different decisions.","PeriodicalId":330324,"journal":{"name":"2009 Ninth International Conference on Intelligent Systems Design and Applications","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131585168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bayesian Networks represent one of the most successful tools for medical diagnosis and therapies follow-up. We present an algorithm for Bayesian network structure learning, that is a variation of the standard search-and-score approach. The proposed approach overcomes the creation of redundant network structures that may include non significant connections between variables. In particular, the algorithm finds which relationships between the variables must be prevented, by exploiting the binarization of a square matrix containing the mutual information (MI) among all pairs of variables. Four different binarization methods are implemented. The MI binary matrix is exploited as a preconditioning step for the subsequent greedy search procedure that optimizes the network score, reducing the number of possible search paths in the greedy search. Our approach has been tested on two different medical datasets and compared against the standard search-and-score algorithm as implemented in the DEAL package.
{"title":"Improved Learning of Bayesian Networks in Biomedicine","authors":"A. Meloni, A. Ripoli, V. Positano, L. Landini","doi":"10.1109/ISDA.2009.163","DOIUrl":"https://doi.org/10.1109/ISDA.2009.163","url":null,"abstract":"Bayesian Networks represent one of the most successful tools for medical diagnosis and therapies follow-up. We present an algorithm for Bayesian network structure learning, that is a variation of the standard search-and-score approach. The proposed approach overcomes the creation of redundant network structures that may include non significant connections between variables. In particular, the algorithm finds which relationships between the variables must be prevented, by exploiting the binarization of a square matrix containing the mutual information (MI) among all pairs of variables. Four different binarization methods are implemented. The MI binary matrix is exploited as a preconditioning step for the subsequent greedy search procedure that optimizes the network score, reducing the number of possible search paths in the greedy search. Our approach has been tested on two different medical datasets and compared against the standard search-and-score algorithm as implemented in the DEAL package.","PeriodicalId":330324,"journal":{"name":"2009 Ninth International Conference on Intelligent Systems Design and Applications","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134383542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
L. Herrera, M. M. Pérez, J. Santana, R. Pulgar, Jesús González, H. Pomares, I. Rojas
Tooth bleaching is receiving an increasing interest by patients and dentists since it is a relatively non-invasive approach for whitening and lightening teeth. Instrument designed for tooth color measurements and visual assessment with commercial shade guides are nowadays used to evaluate the tooth color. However, the degree of color change after tooth bleaching varied substantially among studies and currently, there are no objective guidelines to predict the effectiveness of a tooth bleaching treatment. Fuzzy Logic is a well known paradigm for data modelling; their main advantage is their ability to provide an interpretable set of rules that can be later used by the scientists. However these models have the problem that the global approximation optimization can lead to a deficient rule local modelling. This work proposes a modified fuzzy model that performs a simultaneous global and local modelling. This property is reached thanks to a special partitioning of the input space in the fuzzy system. The proposed approach is used to approximate a set of color measurements taken after a bleaching treatment using the pre-bleaching measurements. The system uses as rule antecedents the colorimetric values of the VITA commercial shade guide. The expected post-bleaching colorimetric values are immediately obtained from the local models (rules) of the system thanks to the proposed modified fuzzy model. Additionally, these post-bleaching CIELAB coordinate values have been associated with VITA shades through the evaluation of their respective membership functions, approximating which VITA shades are expected after the treatment for each pre-bleaching VITA shade.
{"title":"A Data Mining Approach Based on a Local-Global Fuzzy Modelling for Prediction of Color Change after Tooth Bleaching Using Vita Classical Shades","authors":"L. Herrera, M. M. Pérez, J. Santana, R. Pulgar, Jesús González, H. Pomares, I. Rojas","doi":"10.1109/ISDA.2009.100","DOIUrl":"https://doi.org/10.1109/ISDA.2009.100","url":null,"abstract":"Tooth bleaching is receiving an increasing interest by patients and dentists since it is a relatively non-invasive approach for whitening and lightening teeth. Instrument designed for tooth color measurements and visual assessment with commercial shade guides are nowadays used to evaluate the tooth color. However, the degree of color change after tooth bleaching varied substantially among studies and currently, there are no objective guidelines to predict the effectiveness of a tooth bleaching treatment. Fuzzy Logic is a well known paradigm for data modelling; their main advantage is their ability to provide an interpretable set of rules that can be later used by the scientists. However these models have the problem that the global approximation optimization can lead to a deficient rule local modelling. This work proposes a modified fuzzy model that performs a simultaneous global and local modelling. This property is reached thanks to a special partitioning of the input space in the fuzzy system. The proposed approach is used to approximate a set of color measurements taken after a bleaching treatment using the pre-bleaching measurements. The system uses as rule antecedents the colorimetric values of the VITA commercial shade guide. The expected post-bleaching colorimetric values are immediately obtained from the local models (rules) of the system thanks to the proposed modified fuzzy model. Additionally, these post-bleaching CIELAB coordinate values have been associated with VITA shades through the evaluation of their respective membership functions, approximating which VITA shades are expected after the treatment for each pre-bleaching VITA shade.","PeriodicalId":330324,"journal":{"name":"2009 Ninth International Conference on Intelligent Systems Design and Applications","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134583606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Claudia d’Amato, N. Fanizzi, F. Esposito, Thomas Lukasiewicz
We present a classification method, founded in the emph{instance-based learning} and the emph{disjunctive version space} approach, for performing approximate retrieval from knowledge bases expressed in Description Logics. It is able to supply answers, even though they are not logically entailed by the knowledge base (e.g. because of its incompleteness or when there are inconsistent assertions). Moreover, the method may also induce new knowledge that can be employed to make the ontology population task semi-automatic. The method has been experimentally tested showing that it is sound and effective.
{"title":"Inductive Query Answering and Concept Retrieval Exploiting Local Models","authors":"Claudia d’Amato, N. Fanizzi, F. Esposito, Thomas Lukasiewicz","doi":"10.1109/ISDA.2009.34","DOIUrl":"https://doi.org/10.1109/ISDA.2009.34","url":null,"abstract":"We present a classification method, founded in the emph{instance-based learning} and the emph{disjunctive version space} approach, for performing approximate retrieval from knowledge bases expressed in Description Logics. It is able to supply answers, even though they are not logically entailed by the knowledge base (e.g. because of its incompleteness or when there are inconsistent assertions). Moreover, the method may also induce new knowledge that can be employed to make the ontology population task semi-automatic. The method has been experimentally tested showing that it is sound and effective.","PeriodicalId":330324,"journal":{"name":"2009 Ninth International Conference on Intelligent Systems Design and Applications","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133276931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Asynchronous discussion forum can provide a platform for online learners to communicate with one another easily, without the constraint of place and time. This study explores the analysis process of online asynchronous discussion. We focus upon content analysis and social network analysis, which is the technique often used to measure online discussion in formal educational settings. In addition, Soller’s model for content analysis was developed and employed to qualitatively analyze the online discussion. We also discuss the use of network indicators of social network analysis to assess level participation and communication structure throughout online discussion. Adjacency matrix, graph theory and network analysis techniques were applied to quantitatively define the networks interaction among students. The findings showed that these methods provide more meaningful students’ interaction analysis in term of information of communication transcripts and communication structures in online asynchronous discussion.
{"title":"Analyzing Online Asynchronous Discussion Using Content and Social Network Analysis","authors":"B. Erlin, N. Yusof, Azizah Abdul Rahman","doi":"10.1109/ISDA.2009.40","DOIUrl":"https://doi.org/10.1109/ISDA.2009.40","url":null,"abstract":"Asynchronous discussion forum can provide a platform for online learners to communicate with one another easily, without the constraint of place and time. This study explores the analysis process of online asynchronous discussion. We focus upon content analysis and social network analysis, which is the technique often used to measure online discussion in formal educational settings. In addition, Soller’s model for content analysis was developed and employed to qualitatively analyze the online discussion. We also discuss the use of network indicators of social network analysis to assess level participation and communication structure throughout online discussion. Adjacency matrix, graph theory and network analysis techniques were applied to quantitatively define the networks interaction among students. The findings showed that these methods provide more meaningful students’ interaction analysis in term of information of communication transcripts and communication structures in online asynchronous discussion.","PeriodicalId":330324,"journal":{"name":"2009 Ninth International Conference on Intelligent Systems Design and Applications","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133324379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The adequate and rational drugs selection is considered one of the main objectives in Hospital scenarios. The drugs evaluation for their inclusion in the Hospital Pharmacy requires considering multiple evaluation aspects and criteria where different people are involved with different roles, valuations and preferences with the aim of analyzing a great number of factors and characteristics from a huge number of resources with imprecise assessments. This paper presents a consensus decision model combining quantitative information with fuzzy multigranular linguistic information to support the selection of drugs for their inclusion in the Hospital Universitario Virgen de la Victoria from Málaga.
{"title":"Definition of a Consensual Drug Selection Process in Hospital Universitario Virgen de la Victoria","authors":"Jesús M. Doña Fernánde, I. Moya, J. López","doi":"10.1109/ISDA.2009.94","DOIUrl":"https://doi.org/10.1109/ISDA.2009.94","url":null,"abstract":"The adequate and rational drugs selection is considered one of the main objectives in Hospital scenarios. The drugs evaluation for their inclusion in the Hospital Pharmacy requires considering multiple evaluation aspects and criteria where different people are involved with different roles, valuations and preferences with the aim of analyzing a great number of factors and characteristics from a huge number of resources with imprecise assessments. This paper presents a consensus decision model combining quantitative information with fuzzy multigranular linguistic information to support the selection of drugs for their inclusion in the Hospital Universitario Virgen de la Victoria from Málaga.","PeriodicalId":330324,"journal":{"name":"2009 Ninth International Conference on Intelligent Systems Design and Applications","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128973839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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