A prediction model for Obstructive Sleep Apnea (OSA) is developed based on a novel formulation ap... more A prediction model for Obstructive Sleep Apnea (OSA) is developed based on a novel formulation approach by using customized Associative Rule (AR) Mining Techniques, i.e. Adaptive Apriori (AA) and Weighted Association Rule Mining (WARM), on visual inspected variables. This prediction model is based on the typical clinical data sets obtained from several hospitals where from derivation of association rule mining (data-driven) techniques and medical knowledge on these variables (knowledge-driven) were applied separately to our training data sets. Application of our prediction framework to our testing data sets showed a significant improvement in terms of prediction accuracy and level of efficiency as compared with the classical approach of using medical Experts’ Rules (ERs).
We present the development of a prototype system called Angur, which is designed and built for vi... more We present the development of a prototype system called Angur, which is designed and built for visualization of XML documents. There two main motivations of this work: firstly is to allow the users to explore and manipulate XML documents and secondly is to display the search results graphically, in two or three dimensions, grouped by topic or category. This prototype employs modern interactive visualization techniques to provide a visual presentation of a set of XML documents. The motivation and evaluation of several design features, such as keyword to concept mapping, explicit clustering, the use of 3-D vs. 2-D, and the relationship of visualization to logical structure are described.
Complex data structures have been used in many applications that can make them difficult to under... more Complex data structures have been used in many applications that can make them difficult to understand and manage. Visualization of these structures allows a user to get better insight both in the data structure and in the application itself. In this work, we present a visualization system, called Angur, for the structured data-oriented XML formats. We used a graphical representation that is based on tree maps. This type of visualization is usually referred to as tree rewriting. It allows efficient filtration and transformation of the document tree to fit particular user needs. In particular, our system allows the transformation of XML documents to a structure of a graphical network of objects. These visualization objects can be easily analysed, interpreted and managed without the need of dealing with their deep representations.
Characteristics of Support Vector Machine (SVM) and its classifications are elaborated to show wh... more Characteristics of Support Vector Machine (SVM) and its classifications are elaborated to show why incorporation of newly proposed and formulated regularization on feature selections based on correlation studies are necessary to achieve a better prediction or classification. Feature selections based on correlation studies are incorporated into the proposed formulations for the weighting portions of the objective functions for SVM. Proposed cfsw-SVM algorithms arethen developed. Proposed formulations on SVM regularization parameter provides synergistic adjustments between prediction or classification accuracy and the level of correlations among features in the SVM implemented. Prediction and/or classification accuracies of cfsw-SVM algorithms are significantly improved.
This research develops a knowledge-based system by using computational intelligent approaches bas... more This research develops a knowledge-based system by using computational intelligent approaches based on Boosting algorithms on decision trees augmented by pruning techniques and Association Rule Mining. This system can provide better prediction accuracies and speedier medical analyses in order to help medical doctors in the earlier clinical diagnoses of Obstructive Sleep Apnea, i.e. OSA. The prediction algorithms developed are based on the OSA datasets collected mainly from the public hospitals in Selangor, Malaysia. The proposed OSA questionnaires have been newly designed after the data collection has been completed. The newly proposed and designed OSA questionnaires are customizable to best fit for Malaysians and have significant differences with the internationally standardized OSA questionnaires since these questionnaires are tailor-made based on the raw data collected within populations in Malaysia only. The parameters involved in the prediction algorithms developed are based on...
Incorporation of the structural risk minimization of Support Vector Machine to pre-prune the deci... more Incorporation of the structural risk minimization of Support Vector Machine to pre-prune the decision trees based on empirical risk minimization is conducted to develop a combined algorithm. It is named as Support Vector Machine Pruned Decision Trees (SVMPDT) algorithm. Pre-pruning of decision trees (DT) is applied to the datasets through the synergistically adjusted regularization parameter of SVM. This is done by the proposed new approach derived from the study on the synergy effects between the pre-pruning weighting fraction of DT and the regularization parameter of SVM. The regularization parameter of SVM is customized and adjusted based on the different features and characteristics of DT from each applied dataset. After applying the proposed algorithms to the assigned datasets, it is shown to be more accurate in classification when compared with typical SVM without getting its parameter adjusted accordingly and the typical DT classification without applying pre-pruned weighting...
Based on the datasets from UCI and Obstructive Sleep Apnea, a disparate methodology of uncovering... more Based on the datasets from UCI and Obstructive Sleep Apnea, a disparate methodology of uncovering the visualization effects into the pushed support constraints of schema enumerated tree-based classification techniques is proposed and presented in this paper. This is to actively ‘wipe out’ the redundant growing effects of decision trees through itemset generation when visualization techniques are applied using Principal Component Analysis (PCA) and/or Principal Component Variable Grouping (PCVG) algorithms. Enumeration specification is based on the schema enumerated tree (SET) drawn after sorting out the features and characteristics on each dataset applied. The linchpin is to streamline the pre-tree classification effects for post-tree classification by using visualization techniques, i.e. PCA and/or PCVG, which are applied during the SET development. The over-fitting effects done during the SET development by the pushed support constraints can be counter-corrected by fewer PCA and/o...
Boosted Association-Ruled Pruned Decision Tree (ARP-DT), the improved version of the Boosted Deci... more Boosted Association-Ruled Pruned Decision Tree (ARP-DT), the improved version of the Boosted Decision Tree algorithm, was developed by using association-ruled pre-and post-pruning techniques with referring to the pushed minimum support and minimum confidence constraints as well as the association rules applied. The novelty of the Association-Ruled pruning techniques applied mainly embark on the pre-pruning techniques through researching on the maximum number of decision tree splitting, as well as the post-pruning techniques involving subtree replacement and subtree raising. The applied association rules (ARs) augment the mining of frequent itemset (s) or interesting itemset (s) such that appropriate pre-pruning or subtree pruning techniques can be applied before AdaBoost ensemble is implemented. The ARs applied involve the Adaptive Apriori (AA) augmented rule definitions and theorem as stated in this research focuses on the characteristics of the datasets accessed so as to streamlin...
2011 7th International Conference on Information Technology in Asia, 2011
Human-Computer Interaction (HCI) techniques are important in visualization because a good combina... more Human-Computer Interaction (HCI) techniques are important in visualization because a good combination of them can help users to design a good visualization system while optimizing its visualization effects. In order to incorporate different HCI techniques to 'work together' to achieve the synergy effects for optimizing graphical scalable visualization, three of them, i.e. goal, task and scenario analyses, are applied to
Haya Shida, Subscribe (Full Service), Register (Limited Service, Free), Login. Search: The ACM Di... more Haya Shida, Subscribe (Full Service), Register (Limited Service, Free), Login. Search: The ACM Digital Library The Guide. ...
A prediction model for Obstructive Sleep Apnea (OSA) is developed based on a novel formulation ap... more A prediction model for Obstructive Sleep Apnea (OSA) is developed based on a novel formulation approach by using customized Associative Rule (AR) Mining Techniques, i.e. Adaptive Apriori (AA) and Weighted Association Rule Mining (WARM), on visual inspected variables. This prediction model is based on the typical clinical data sets obtained from several hospitals where from derivation of association rule mining (data-driven) techniques and medical knowledge on these variables (knowledge-driven) were applied separately to our training data sets. Application of our prediction framework to our testing data sets showed a significant improvement in terms of prediction accuracy and level of efficiency as compared with the classical approach of using medical Experts’ Rules (ERs).
We present the development of a prototype system called Angur, which is designed and built for vi... more We present the development of a prototype system called Angur, which is designed and built for visualization of XML documents. There two main motivations of this work: firstly is to allow the users to explore and manipulate XML documents and secondly is to display the search results graphically, in two or three dimensions, grouped by topic or category. This prototype employs modern interactive visualization techniques to provide a visual presentation of a set of XML documents. The motivation and evaluation of several design features, such as keyword to concept mapping, explicit clustering, the use of 3-D vs. 2-D, and the relationship of visualization to logical structure are described.
Complex data structures have been used in many applications that can make them difficult to under... more Complex data structures have been used in many applications that can make them difficult to understand and manage. Visualization of these structures allows a user to get better insight both in the data structure and in the application itself. In this work, we present a visualization system, called Angur, for the structured data-oriented XML formats. We used a graphical representation that is based on tree maps. This type of visualization is usually referred to as tree rewriting. It allows efficient filtration and transformation of the document tree to fit particular user needs. In particular, our system allows the transformation of XML documents to a structure of a graphical network of objects. These visualization objects can be easily analysed, interpreted and managed without the need of dealing with their deep representations.
Characteristics of Support Vector Machine (SVM) and its classifications are elaborated to show wh... more Characteristics of Support Vector Machine (SVM) and its classifications are elaborated to show why incorporation of newly proposed and formulated regularization on feature selections based on correlation studies are necessary to achieve a better prediction or classification. Feature selections based on correlation studies are incorporated into the proposed formulations for the weighting portions of the objective functions for SVM. Proposed cfsw-SVM algorithms arethen developed. Proposed formulations on SVM regularization parameter provides synergistic adjustments between prediction or classification accuracy and the level of correlations among features in the SVM implemented. Prediction and/or classification accuracies of cfsw-SVM algorithms are significantly improved.
This research develops a knowledge-based system by using computational intelligent approaches bas... more This research develops a knowledge-based system by using computational intelligent approaches based on Boosting algorithms on decision trees augmented by pruning techniques and Association Rule Mining. This system can provide better prediction accuracies and speedier medical analyses in order to help medical doctors in the earlier clinical diagnoses of Obstructive Sleep Apnea, i.e. OSA. The prediction algorithms developed are based on the OSA datasets collected mainly from the public hospitals in Selangor, Malaysia. The proposed OSA questionnaires have been newly designed after the data collection has been completed. The newly proposed and designed OSA questionnaires are customizable to best fit for Malaysians and have significant differences with the internationally standardized OSA questionnaires since these questionnaires are tailor-made based on the raw data collected within populations in Malaysia only. The parameters involved in the prediction algorithms developed are based on...
Incorporation of the structural risk minimization of Support Vector Machine to pre-prune the deci... more Incorporation of the structural risk minimization of Support Vector Machine to pre-prune the decision trees based on empirical risk minimization is conducted to develop a combined algorithm. It is named as Support Vector Machine Pruned Decision Trees (SVMPDT) algorithm. Pre-pruning of decision trees (DT) is applied to the datasets through the synergistically adjusted regularization parameter of SVM. This is done by the proposed new approach derived from the study on the synergy effects between the pre-pruning weighting fraction of DT and the regularization parameter of SVM. The regularization parameter of SVM is customized and adjusted based on the different features and characteristics of DT from each applied dataset. After applying the proposed algorithms to the assigned datasets, it is shown to be more accurate in classification when compared with typical SVM without getting its parameter adjusted accordingly and the typical DT classification without applying pre-pruned weighting...
Based on the datasets from UCI and Obstructive Sleep Apnea, a disparate methodology of uncovering... more Based on the datasets from UCI and Obstructive Sleep Apnea, a disparate methodology of uncovering the visualization effects into the pushed support constraints of schema enumerated tree-based classification techniques is proposed and presented in this paper. This is to actively ‘wipe out’ the redundant growing effects of decision trees through itemset generation when visualization techniques are applied using Principal Component Analysis (PCA) and/or Principal Component Variable Grouping (PCVG) algorithms. Enumeration specification is based on the schema enumerated tree (SET) drawn after sorting out the features and characteristics on each dataset applied. The linchpin is to streamline the pre-tree classification effects for post-tree classification by using visualization techniques, i.e. PCA and/or PCVG, which are applied during the SET development. The over-fitting effects done during the SET development by the pushed support constraints can be counter-corrected by fewer PCA and/o...
Boosted Association-Ruled Pruned Decision Tree (ARP-DT), the improved version of the Boosted Deci... more Boosted Association-Ruled Pruned Decision Tree (ARP-DT), the improved version of the Boosted Decision Tree algorithm, was developed by using association-ruled pre-and post-pruning techniques with referring to the pushed minimum support and minimum confidence constraints as well as the association rules applied. The novelty of the Association-Ruled pruning techniques applied mainly embark on the pre-pruning techniques through researching on the maximum number of decision tree splitting, as well as the post-pruning techniques involving subtree replacement and subtree raising. The applied association rules (ARs) augment the mining of frequent itemset (s) or interesting itemset (s) such that appropriate pre-pruning or subtree pruning techniques can be applied before AdaBoost ensemble is implemented. The ARs applied involve the Adaptive Apriori (AA) augmented rule definitions and theorem as stated in this research focuses on the characteristics of the datasets accessed so as to streamlin...
2011 7th International Conference on Information Technology in Asia, 2011
Human-Computer Interaction (HCI) techniques are important in visualization because a good combina... more Human-Computer Interaction (HCI) techniques are important in visualization because a good combination of them can help users to design a good visualization system while optimizing its visualization effects. In order to incorporate different HCI techniques to 'work together' to achieve the synergy effects for optimizing graphical scalable visualization, three of them, i.e. goal, task and scenario analyses, are applied to
Haya Shida, Subscribe (Full Service), Register (Limited Service, Free), Login. Search: The ACM Di... more Haya Shida, Subscribe (Full Service), Register (Limited Service, Free), Login. Search: The ACM Digital Library The Guide. ...
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Papers by Doreen Sim