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 9 of 9 for “"misclassification error"”.
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Incorporating game theory with soft sets for better decision making
… different parameters, resulting in a decrease in misclassification error in an environment involving uncertainty. Furthermore, the extent of the decrease can be fine-tuned by adjusting the ratio between the cost for misclassification error and the cost for undecided error. Based on the user’s …
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An improved algorithm for iris classification by using support vector machine and binary random machine learning
… average detection rate, average prevalence and misclassification error rate (MER) were used by refers confusion matrix values output during data analysis for average and individual performance of each classifier. Besides that, Performance Visualization such as Stacked Bar Plot, Fourfold Plot, …
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Postmarket sequential database surveillance of medical products
… medical product adoption and utilization, misclassification error, and the unknown true excess risk in the environment. Using vaccine examples and the simulator to illustrate, this dissertation first demonstrates the tradeoffs associated with sample size calculations in sequential …
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Systems Pharmacology – Machine Learning Approaches in Profiling Oncology Drug Candidates
… ensemble random forest produced the lowest mean misclassification error.
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Morpho-colorimetric and non-parametric analysis in statistical classification of vascular flora
… considered, CA allowed to reduce of 25% the misclassification error obtained by the best of the four classifiers. Finally, approach aimed at evaluating the reliability of a classification rule has been proposed. The algorithms proposed are developed and optimized for botanical seeds, but they …
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Impact of financial distress on UK bank performance and customer loyalty : an empirical study.
… crisis periods. Yet, Altman‘s model had high misclassification error rate and less predictive power during the crisis than before and afterwards. With regards to the performance of banks, the result revealed that banks performed better in terms of profitability, liquidity and activity ratios …
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Modeling Point Patterns, Measurement Error and Abundance for Exploring Species Distributions
… and then we adjust for measurement error, hence misclassification error, to yield the observed abundance classifications. With data on a regular grid over CFR, the analysis is done with a conditionally autoregressive prior on spatial random effects. With around ~ 37000 cells to work …
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Measurement and prediction of inpatient case manager workload in a tertiary hospital setting
… low workload with an accuracy of 81%. Two class misclassification error rates (high-as-low or low-as-high) of 7% can currently be achieved. Finally, in a synthesis of all of our work, we present the outline for a dynamic case assignment scheme based on pooling and balancing the number of cases in …
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Some Advances in Classifying and Modeling Complex Data
… need to be able to accommodate more than one error terms. In Chapter 4, I propose a variance component mixed model for a nano material experiment data to address the between group, within group and within subject variance components into a single model. To adjust possible systematic error …