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 10 of 10 for “"meta-classifier"”.
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A context-sensitive meta-classifier for color-naming
… as a whole. This algorithm is an incremental meta-learner, leveraging a generic online-learner and adding context-sensitivity. A human study is presented, assessing the extent of semantic contextual effects on color naming. An evaluation of the algorithm based on the corpus gathered in this …
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Component-wise analysis of metaheuristic algorithms for novel fuzzy-meta classifier
Metaheuristic research has proposed promising results in science, business, and engineering problems. But, mostly high-level analysis is performed on metaheuristic performances. This leaves several critical questions unanswered due to black-box issue that does not reveal why certain metaheuristic …
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Improving information extraction by acquiring external evidence with reinforcement learning
… traditional extractors and a competitive meta-classifier baseline
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Vision-based terrain classification and classifier fusion for planetary exploration rovers
… for merging the results of these "low level" classifiers are presented that rely on Bayesian fusion and meta-classifier fusion. The performances of these algorithms are studied using images from NASA's Mars Exploration Rover mission and through experiments on a four-wheeled test-bed rover …
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Predicting the risk for postoperative delirium using routine EEG monitoring data
… choice created profound EEG differences that classifiers initially exploited as POD proxies rather than detecting genuine vulnerability. Training medication-specific models eliminated these pharmacological confounds. All three EEG features captured meaningful vulnerability patterns. The …
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The Search for a Cost Matrix to Solve Rare-Class Biological Problems
… to the rare-class problem. This solution uses MetaCost, a cost-sensitive meta-classifier, that takes in a classification algorithm, training data, and a cost matrix. This cost matrix adjusts the learning of the classification algorithm to classify more of the rare-class data but is generally …
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Grounding natural language with autonomous interaction
… over traditional extractors and a competitive meta-classifier baseline.
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An Exploration of Multimodal Document Classification Strategies
… proliferates in modern documents. We design meta-classification schemes that combine and integrate state-of-the-art text and image feature-extractors with state-of-the-art classifiers. Meta-classifiers fuse information across modalities that differ in nature and hence have more information on …
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Ensemble-based Supervised Learning for Predicting Diabetes Onset
… Ensembles often perform better than a single classifier, and accuracy and diversity have been highlighted as the two vital requirements for constructing good ensemble classifiers. Experiments in this thesis explore the relationship between diversity from heterogeneous ensemble classifiers and …
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Inferring properties of neural networks with intelligent designs
… in many scenarios such as network log anomaly classifiers leaking data about the network they were trained on, disease detectors revealing information about participants such as genomic markers, facial recognition classifiers revealing data about the faces it was trained on, just to name a few …