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 20 of 643 for “"machine learning algorithms"”.
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High-throughput machine learning algorithms
The field of machine learning has become strongly compute driven, such that emerging research and applications require larger amounts of specialised hardware or smarter algorithms to advance beyond the state-of-the-art. This thesis develops specialised techniques and algorithms for a subset of …
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Stability of machine learning algorithms
… is often the primary criterion for evaluating a learning algorithm. In this thesis, I will introduce novel concepts of stability into the machine learning community. A learning algorithm is said to be stable if it produces consistent predictions with respect to small perturbation of training …
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Meta-RaPS Hybridization with Machine Learning Algorithms
… known as Meta-RaPS, by integrating it with machine learning algorithms. Introducing a new metaheuristic algorithm starts with demonstrating its performance. This is accomplished by using the new algorithm to solve various combinatorial optimization problems in their basic form. The next …
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Machine Learning Algorithms for Improved Glaucoma Diagnosis
… of advanced statistical techniques based on machine learning for automated classification of tests from visual field examinations and retinal nerve fibre measurements to detect glaucoma. Diagnostic performance of the applied machine learning classification algorithms was shown to depend …
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Fairness and Privacy in Machine Learning Algorithms
… nearly impossible but with the widespread use of machine learning algorithms and their ability to process enormous data in a fast, cost-effective, and scalable way has proven to be a preferred choice to glean useful insights and solve business problems in many domains. With this widespread use of …
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Probabilistic machine learning algorithms for molecule discovery
… information will be gained from each test. In machine learning, this approach is typically called Bayesian optimisation and has been studied for many other problems, such as tuning hyperparameters of machine learning models. Although in principle Bayesian optimisation can be straightforwardly …
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Machine Learning Algorithms for Geometry Processing by Example
This thesis proposes machine learning algorithms for processing geometry by example. Each algorithm takes as input a collection of shapes along with exemplar values of target properties related to shape processing tasks. The goal of the algorithms is to output a function that maps from the shape …
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Classification of customer complaints using machine learning algorithms
… and classifying time. This research uses five ML algorithms namely: LR, SVM, LightGB, KNN, and CART DT to assess how text classification technology can be used to improve the classification of customer complaints in the financial services industry by assessing how accurately would the algorithms …
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Machine Learning Algorithms and Applications in Health Care
There have been many recent advances in machine learning, resulting in models which have had major impact in a variety of disciplines. Some of the best performing models are black boxes, which are not directly interpretable by humans. However, in some applications such as health care it is vital to …
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Analysis of Machine Learning Algorithms for Time Series Prediction
… there has been increased interest in applying machine learning algorithms to time series prediction problems. There are many machine learning algorithms that can be used for time series prediction problems but selecting an algorithm can be challenging due to algorithms not being suitable to all …
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Novel Machine Learning Algorithms for Personalized Medicine and Insurance
… computational performance is improved, and new algorithms are developed, machine learning has been viewed as the key analytical tool that will advance healthcare delivery. Nevertheless, until recently, despite the enthusiasm about the potential of “big data”, only a few examples have impacted …
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Applicant justice perceptions of machine learning algorithms in personnel selection
Machine-learning artificial intelligence algorithms provide organizations with the opportunity to quickly and efficiently process information about potential employees while reducing costs associated with selection and turnover. However, any bias or error present in the programming of such …
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Improving prediction of opioid use disorder with machine learning algorithms
… in better prediction accuracy using various machine learning classification algorithms. To build a labeled dataset, responses from the 2018 and 2019 edition of the National Survey on Drug Use and Health (NSDUH) were collected. This dataset was used to train and test several classification …
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Machine learning algorithms and experimentation methods applied to sample quantification
Existe una creciente demanda de métodos eficientemente rentables para la estimación de la distribución de las clases en una muestra de individuos. Una tarea de aprendizaje automático recientemente formalizada como cuantificación. Su principal objetivo es la estimación precisa del número de casos …
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Development and evaluation of machine learning algorithms for biomedical applications
… existing approaches. This dissertation develops machine learning and data mining algorithms, and applies these algorithms to solve the two important biomedical problems. Specifically, to tackle the gene network inference problem, the dissertation proposes (i) new techniques for selecting …
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Development of machine learning algorithms for screening of pulmonary disease
… structure. Using this structure, the PFT machines produced good results on each classification layer: Healthy vs. Unhealthy [AUC=0.90 (0.04)], Obstructive (Obs.) vs. Non-obstructive [AUC=0.95 (0.05)], Obs. AR vs. Obs. Non-AR [AUC=0.72 (0.10)], COPD + AR vs. Asthma + AR [AUC=0.95 (0.15)], …
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