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 13 of 13 for “"linear classifier"”.
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The application of neural networks to communication channel equalisation : a comparison between localised and non-localised basis functions
… equaliser. A neural network is essentially a non-linear classifier; in general a neural network is able to classify data by employing a non-linear function. The primary subject of this dissertation is the comparative performance of neural networks employing non-localised basis (non-linear) …
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Characterizing and predicting enhancers in the human genome
… regulatory sequences. By training a generalized linear classifier on this data, we created a predictor for enhancer sequences that achieved 70% accuracy.
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Comparing learned representations of deep neural networks
… in a high dimensional space and applying a linear classifier in this space. This work focuses on comparing these representations as well as the learned input features for different state-of-the-art convolutional neural network architectures. By focusing on the geometry of this …
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Techniques in support vector classification
… feature selection uses a novel combination of a linear classifier known as Fisher's discriminant and a nonlinear (polynomial) map known as the Veronese map. We apply our method to a problem in materials design. Our second problem concerns the selection of the kernel k : Rn x Rn → R in (*). For …
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Computational Framework Enabling an EEG-based BCI for Neurofeedback in Language Disorders: The case of dyslexia
… condition (connected speech). The second was a linear classifier which predicted dyslexia status (0.77 AUC). This classifier was based on supervised spatial filtering of delta-band oscillations, showing useful features to classify dyslexic neural patterns both across connected speech and …
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Topics in dimension reduction and missing data in statistical discrimination.
… In the first chapter, we define the concept of linear dimension reduction, review some popular linear dimension reduction procedures, discuss background research that we use in chapters two and three, and give a brief outline of the dissertation contents. In chapter two, we derive a linear …
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Classification of tinnitus versus non-tinnitus hearing impaired subject fMRI data
… activity within the data point over time. Then a linear or non-linear classifier, an algorithm that trains itself by building a probability profile for how likely each feature will be to belong to a cluster group, given a target or control class (in the case of this study, tinnitus or non-tinnitus …
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A robust region-adaptive digital image watermarking system
… the region-adaptive watermarking algorithm in a linear classifier. The experiment conducted to validate this feature shows that, on average, 94.5% of all watermark attacks can be correctly detected and identified.
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An Investigation into the Performance of Ethnicity Verification Between Humans and Machine Learning Algorithms
… models for redundant information removal, and a linear classifier for the binary task. The experimental results concluded that the facial profile image of a Pakistani face is distinct amongst other ethnicities. However, the methodology consisted of limitations for example, low performance …
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An Investigation into the Performance of Ethnicity Verification Between Humans and Machine Learning Algorithms
… models for redundant information removal, and a linear classifier for the binary task. The experimental results concluded that the facial profile image of a Pakistani face is distinct amongst other ethnicities. However, the methodology consisted of limitations for example, low performance …
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New models and methods for classification and feature selection. a mathematical optimization perspective
… Benchmarking. Regarding the first one, the SVM classifier is based on the search for the separating hyperplane of maximum margin and it is written as a quadratic convex problem. In the Benchmarking context, the goal is to calculate the different efficiencies through a non-parametric …
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Website Structure
… structure were found to be identifiable by linear classifiers, when trained on features of the website hypertext graphs. Two more structural types, not analyzed with the classifiers, were suggested through an examination of misclassified websites. Further, the notion of website structure was …
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Some Advances in Classifying and Modeling Complex Data
… Among various classification methods, linear classifiers have been widely used because of computational advantages, ease of implementation and interpretation compared with non-linear classifiers. Specifically, linear discriminant analysis (LDA) is one of the most important methods in …