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Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Oversampling Methods For Imbalanced Dataset Classification And Their Application To Gynecological Disorder Diagnosis, Iman Nekooeimehr
Oversampling Methods For Imbalanced Dataset Classification And Their Application To Gynecological Disorder Diagnosis, Iman Nekooeimehr
USF Tampa Graduate Theses and Dissertations
In many applications, the dataset for classification may be highly imbalanced where most of the instances in the training set may belong to some of the classes (majority classes), while only a few instances are from the other classes (minority classes). Conventional classifiers will strongly favor the majority class and ignore the minority instances. The imbalance problem can occur in both binary data classification and also in ordinal regression. Ordinal regression is a supervised approach for learning the ordinal relationship between classes. Extensive research has been performed for addressing imbalanced datasets for binary classification; however, current methods do not address …
Spatiotemporal Sensing And Informatics For Complex Systems Monitoring, Fault Identification And Root Cause Diagnostics, Gang Liu
USF Tampa Graduate Theses and Dissertations
In order to cope with system complexity and dynamic environments, modern industries are investing in a variety of sensor networks and data acquisition systems to increase information visibility. Multi-sensor systems bring the proliferation of high-dimensional functional Big Data that capture rich information on the evolving dynamics of natural and engineered processes. With spatially and temporally dense data readily available, there is an urgent need to develop advanced methodologies and associated tools that will enable and assist (i) the handling of the big data communicated by the contemporary complex systems, (ii) the extraction and identification of pertinent knowledge about the environmental …