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 11 of 11 for “"kNN algorithm."”.
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KNN Optimization for Multi-Dimensional Data
<p>The K-Nearest Neighbors (KNN) algorithm is a simple but powerful technique used in the field of data analytics. It uses a distance metric to identify existing samples in a dataset which are similar to a new sample. The new sample can then be classified via a class majority voting of its most …
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The comparative study of model-based and appearance based gait recognition for leave bag behind
… which is Support Vector Machine (SVM) and KNN (K nearest Neighbour) based on accuracy and misclassification rates (MER) metrics. The experiment results show that the accuracy and misclassification rate (MER) of Appearance-based approaches obtained is 93.66% and 6.33% respectively tested on …
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Brief Study of Classification Algorithms in Machine Learning
… of three most commonly used Machine Learning algorithms: k-Nearest Neighbors (kNN), Decision Trees and Naïve Bayes. All these algorithms fall under the Classification algorithm category of Unsupervised Machine Learning. This paper is constructed structurally in explaining the working theory …
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Automatic fall risk detection based on imbalanced data
… propose a pose estimation-based fall detection algorithm to detect fall risks. Since fall data is rare in real-world situations, we train and evaluate our approach in a highly imbalanced data setting. We assess not only different imbalanced data handling methods, but also different machine …
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Machine learning in astronomy
… In this thesis we test various machine learning algorithms and show that many of them can match the human hand scanner performance in classifying transient difference g, r and i-band imaging data from the SDSS-II SN Survey into real objects and artefacts. Using principal component analysis and …
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Machine Learning Classification of Gas Chromatography Data
… techniques for enhancing the performance of ML algorithms. Feature Selection is a technique for improving performance by using a specific subset of the data. Feature Engineering is a technique to transform the data to make processing more effective. Data Fusion is a technique which combines …
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Model fusion for improving hypoxia forecasts in Corpus Christi Bay, TX, USA: A study of boosting and historical scenario modeling
… modeling and boosting both a k-nearest neighbor (KNN) algorithm and the historical scenario model. Existing data-driven k-nearest neighbor and physics-based valve models are used as the basis for the model fusion. The historical scenario model combines the k-nearest neighbor algorithm with the …
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Psychophysiological Monitoring of Crew State for Extravehicular Activity
… were created using the K Nearest Neighbor (KNN) algorithm. The contributions of this dissertation span the simulation, characterization, and modeling of cognitive state. Ultimately, this work tests the limits of extending laboratory psychophysiological monitoring to more realistic …
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The Development of a Reduced Order Model for Prediction of Haemodynamic and Biochemical Changes in a Computational Cerebral Aneurysm Thrombosis Model
… reduced-order models using machine learning algorithms. Multiple polynomial regression and logistic regression machine learning algorithms were used to predict clot size in patients. The K-nearest neighbours algorithm was used to develop a model that classifies patients' clotting profiles. …
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Coupled similarity analysis in supervised learning
… is widely used in a lot of classification algorithms. When calculating the categorical data similarity, the strategy used by the traditional classifiers often overlooks the inter-relationship between different data attributes and assumes that they are independent of each other. This can be …
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The Exploration of KNN-based Neural Control of Pneumatically Actuated Artificial Muscle
… of neural control through K-Nearest Neighbor (KNN) sorting and the incremental development of a biomimetic actuator in the form of Pneumatic Artificial Muscles (PAMs). KNN classification is a lightweight non-parametric learning algorithm that can rapidly identify and sort an input into …