Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 11 of 11 for “"misclassification costs,"”.
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Elliptical cost-sensitive decision tree algorithm - ECSDT
… in which the task of assessing the impact of the costs associated with different misclassification errors, continues to be one of the major challenging areas for data mining and machine learning. The literature reviews in this area show that most of the cost-sensitive algorithms that have been …
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On Identifying Critical Nuggets Of Information During Classification Task
… metrics - classification accuracy and misclassification costs. Experimental results helped validate that critical nuggets can assist in improving classification accuracies in real world data sets when compared with other standalone classification algorithms. The improvements in accuracy …
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Prediction of going-concern status: a probit model for the auditors
… the literature and the auditors. The effects of misclassification costs of Type I and Type II errors on the Koh model are also considered. It is found that the optimal cut-off probability for the Koh model is very insensitive to varying relative misclassification costs. Coupled with its high …
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Approaches to developing clinically useful Bayesian risk prediction models
… performance with respect to unbalanced misclassification costs. In both simulated and real-world applications, we find our approach to perform favourably in comparison to standard Bayesian methods. We then move to extend the framework to situations where a large number of (potentially …
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Advances in estimation and inference around a biomarker’s true and false classification rates under trichotomous settings
… in trichotomous settings that can accommodate misclassification costs. We apply our approaches to a real data set that involves hepatocellular carcinoma (HCC)patients. HCC is the most common cancer of the liver and the ninth leading cause of cancerrelated death in the United States. Our …
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A Novel Penalized Log-likelihood Function for Class Imbalance Problem
… for mitigating such bias is to penalize the misclassification costs of observations differently in the log-likelihood objective function in the learning process. Existing penalized log-likelihood functions require either hard hyperparameter estimation or high computational complexity. In the …
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Using a Bayesian model for bankruptcy prediction : a comparative approach
… on the accuracy of bankruptcy prediction models. Misclassification can result in erroneous predictions leading to prohibitive costs to firms, investors and the economy. To test the impact of the choice of cut-off points and sampling procedures, three bankruptcy prediction models are assessed- …
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Credit scoring models for Egyptian banks : neural nets and genetic programming versus conventional techniques
… correct classification rates and estimated misclassification costs as criteria. Both advanced scoring techniques, namely, neural nets (probabilistic neural nets and multi-layer feed-forward nets) and genetic programming, and conventional techniques, namely, a weight of evidence measure, …
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Essays on financial reporting quality and auditor attributes
… detecting earnings overstatements when the total misclassification costs are minimised subject to the relative cost of type I versus type II errors. I then contrast the likelihood of type I versus type II errors from this approach with those arising from several widely used measures of unexpected …
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Applications Of Machine Learning In Biology And Medicine
… and practical problem of dealing with different costs during the learning and deployment of classification algorithms.</p> <p>In many applications such as credit fraud detection, network intrusion and specifically medical diagnosis domains, prior class distributions are highly skewed, which makes …
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Understanding thermal comfort and wellbeing of older South Australians using occupant-centric models
… for future investigation, such as the models’ misclassification costs and the integration among wearable sensors, predictors and actuators in the context of older people. In addition, the development of standard protocols necessary for the models’ deployment in real scenarios is prescribed. In …