This paper presents two versions of a general type-2 fuzzy classifier. The focus is on interpretability since the rules are meaningful and the rule base is comprised of few rules, which is a direct consequence of the hierarchical reclassification process being proposed. The approaches are evaluated on a land cover classification problem by using data from a remote sensing platform. The classifiers’ performance are compared with the reference ones’ (maximum likelihood classifier and ordinary fuzzy classifier). The results show that the general type-2 fuzzy modeling is able to produce accurate classifiers while maintaining the model interpretability.
{"title":"Towards Interpretable General Type-2 Fuzzy Classifiers","authors":"Luís A. Lucas, T. M. Centeno, M. Delgado","doi":"10.1109/ISDA.2009.28","DOIUrl":"https://doi.org/10.1109/ISDA.2009.28","url":null,"abstract":"This paper presents two versions of a general type-2 fuzzy classifier. The focus is on interpretability since the rules are meaningful and the rule base is comprised of few rules, which is a direct consequence of the hierarchical reclassification process being proposed. The approaches are evaluated on a land cover classification problem by using data from a remote sensing platform. The classifiers’ performance are compared with the reference ones’ (maximum likelihood classifier and ordinary fuzzy classifier). The results show that the general type-2 fuzzy modeling is able to produce accurate classifiers while maintaining the model interpretability.","PeriodicalId":330324,"journal":{"name":"2009 Ninth International Conference on Intelligent Systems Design and Applications","volume":"19 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":"133824403","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}
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}
R. Grasso, S. Mirra, A. Baldacci, J. Horstmann, M. Coffin, M. Jarvis
This paper describes a procedure to evaluate the performance of ship detection algorithms for Synthetic Aperture Radar (SAR) using real SAR images and Automatic Identification System (AIS) data as ground truth. Accurate AIS-SAR data association is achieved by correcting the AIS data for the SAR induced position errors by exploiting SAR acquisition parameters and vessel state information (speed and course) provided by AIS tracks. The methodology has been tested on a ship detection algorithm based on mathematical morphology which is described in this paper. The evaluation has been carried out on a RADARSAT-2 data set including images at different acquisition modes which was collected in the Mediterranean Sea. Estimates for the detection and the false alarm probability, and the contact position error are provided.
{"title":"Performance Assessment of a Mathematical Morphology Ship Detection Algorithm for SAR Images through Comparison with AIS Data","authors":"R. Grasso, S. Mirra, A. Baldacci, J. Horstmann, M. Coffin, M. Jarvis","doi":"10.1109/ISDA.2009.99","DOIUrl":"https://doi.org/10.1109/ISDA.2009.99","url":null,"abstract":"This paper describes a procedure to evaluate the performance of ship detection algorithms for Synthetic Aperture Radar (SAR) using real SAR images and Automatic Identification System (AIS) data as ground truth. Accurate AIS-SAR data association is achieved by correcting the AIS data for the SAR induced position errors by exploiting SAR acquisition parameters and vessel state information (speed and course) provided by AIS tracks. The methodology has been tested on a ship detection algorithm based on mathematical morphology which is described in this paper. The evaluation has been carried out on a RADARSAT-2 data set including images at different acquisition modes which was collected in the Mediterranean Sea. Estimates for the detection and the false alarm probability, and the contact position error are provided.","PeriodicalId":330324,"journal":{"name":"2009 Ninth International Conference on Intelligent Systems Design and Applications","volume":"148 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":"116338974","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}
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}
The paper presents an application of genetic algorithms to the problem of input variables selection for the design of neural systems. The basic idea of the proposed method lies in the use of genetic algorithms in order to select the set of variables to be fed to the neural networks. However, the main concept behind this approach is far more general and does not depend on the particular adopted model: it can be used for a wide category of systems, also non-neural, and with a variety of performance indicators. The proposed method has been tested on a simple case study, in order to demonstrate its effectiveness. The results obtained in the processing of experimental data are presented and discussed.
{"title":"General Purpose Input Variables Extraction: A Genetic Algorithm Based Procedure GIVE A GAP","authors":"S. Cateni, V. Colla, M. Vannucci","doi":"10.1109/ISDA.2009.190","DOIUrl":"https://doi.org/10.1109/ISDA.2009.190","url":null,"abstract":"The paper presents an application of genetic algorithms to the problem of input variables selection for the design of neural systems. The basic idea of the proposed method lies in the use of genetic algorithms in order to select the set of variables to be fed to the neural networks. However, the main concept behind this approach is far more general and does not depend on the particular adopted model: it can be used for a wide category of systems, also non-neural, and with a variety of performance indicators. The proposed method has been tested on a simple case study, in order to demonstrate its effectiveness. The results obtained in the processing of experimental data are presented and discussed.","PeriodicalId":330324,"journal":{"name":"2009 Ninth International Conference on Intelligent Systems Design and Applications","volume":"49 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":"121973145","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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