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 “"Feature Generation"”.
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Explainability of non-deterministic solvers: explanatory feature generation from the data mining of the search trajectories of population-based metaheuristics.
… an optimisation problem's landscape using generations of solutions that evolve. This diverse set of processes often leads EAs to be considered "Black-Box" in that, due to the stochastic nature of their internal operators, generating an understanding of the reasoning behind EA decisions can …
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Natural Language Processing as a Tool in Supporting Clinical Decision-Making
… machine learning algorithm, be it the method of feature generation or the specific machine learning model chosen for the task. <br/><br/>The results shown in this thesis address this issue by providing a comparative demonstration of multiple feature generation methods alongside a plethora of …
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Meta-Feature Taxonomy for Supporting Automatic Machine Learning
… these frameworks is to initially generate meta-features which are then used as an initial heuristic for further evaluation in recent AutoML frameworks. In this thesis we provide a systematic categorization of meta-features in the AutoML literature. Current implementations of automatic machine …
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Eukaryotic RNA Polymerase II start site detection using artificial neural networks
… neural network (ANN) in conjunction with features that were selected using an information-theoretic approach. Firstly an introduction is given where the problem is described briefly. Some background is given about the biological and genetic principles involved in DNA, RNA and Promoter …
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Predictive Risk Modelling of Hospital Emergency Readmission, and Temporal Comorbidity Index Modelling Using Machine Learning Methods
… administrative data, including data preparation, feature generation and feature selection. Then, the Ensemble Risk Modelling of Hospital Readmission (ERMER) is presented, which is a generative ensemble risk model of hospital readmission model. After that, the Temporal-Comorbidity Adjusted Risk of …
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A Feature-Based Call Graph Distance Measure for Program Similarity Analysis
… propose a call graph distance measure based on features that preserve some structural information from the call graph without explicitly matching user defined functions together. We define basic properties of the features, several ways to compute the feature values, and give a basic algorithm …
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Recognition and investigation of temporal patterns in seismic wavefields using unsupervised learning techniques
… require the parametrization of the data using feature vectors. Applied to seismic recordings, wavefield properties have to be computed from the raw seismograms. For an unsupervised approach, all potential wavefield features have to be considered to reduce subjectivity to a minimum. Furthermore, …
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Imaging-based lensless polarisation-resolving fluid stream analyser for automated, label-free and cost-effective microplastic classification
… learning study with both learned and filter bank feature generation being assessed to aid the microplastic classification process. The FSA and classifier components are used to develop an end-to-end workflow that samples a fluid stream and determines the composition of marine and microplastic …
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Development of Adaptive Tracking Methods with Enhanced Performance Based on Deep Learning
… methods usually adopt an encoder for synchronous feature generation and interaction. Despite their high performance, the approaches tend to feed the encoder full input representations that are highly redundant during training. A novel algorithm MIMTracking is developed for tackling this problem. …
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Fault Detection and Identification of Large-scale Dynamical Systems
… proposed using process data. A high-throughput feature generation concept was applied with a newly proposed feature selection algorithm to prevent the problem with curse of dimensionality. The method was compared to the set of features selected by domain experts. The thesis shows the …
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Flight Data Processing Techniques to Identify Unusual Events
… Because many of the recorded signals (features) are redundant or highly correlated or are very similar in every flight, feature selection techniques are applied to identify those signals that contain the most discriminatory power. In the limited amount of data available to this …
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Stabilising Semiconducting Polymers Using Solid State Molecular Additives
… algorithm uses neural passing networks for feature generation, due to its ability to capture physical plausible features such as functional groups. The algorithm screened over 1.5 billion molecular structures and found plausible molecular structures based on expert knowledge. Fourthly, novel …
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Modelling prognostic trajectories in Alzheimer’s disease
… tools to make such predictions. First, a key feature of AD is the interactive nature of the relationships between biomarkers, such as accumulation of β-amyloid -a peptide that builds plaques between nerve cells-, tau -a protein found in the axons of nerve cells- and widespread …