"support vector classifier" · 6 results

Untethered human motion recognition for a multimodal interface

Ko, Teresa H., 1980-Massachusetts Institute of Technology2003

… approach to model non-linear constraints; a support vector classifier is trained from motion capture data to model the boundary of the space of valid poses. Next, it proposes a system that incorporates body tracking and gesture recognition for an untethered human-computer interface. The …

mit Repository record for Untethered human motion recognition for a multimodal interface (opens in a new tab)

Application of Neural Networks to Inverter-Based Resources

Venkatachari, SidhaarthVirginia Tech2021

… whole. The thesis also proposes a comprehensive support vector classifier (SVC)--based submodule open-circuit fault detection and localization method for modular multilevel converters. This method eliminates the need for extra hardware. Its efficacy is discussed through simulation studies in …

vt Repository record for Application of Neural Networks to Inverter-Based Resources (opens in a new tab)

An analysis of the performance and interpretability of machine learning classification algorithms to predict long-term share returns on the JSE

Boakes, JamieDepartment of Computer Science2024

… algorithms were found to outperform the Support Vector Classifier, Logistic Regression, Decision Tree, Artificial Neural Network, and AdaBoost algorithms. XGBoost and Random Forest were further investigated using SHAP (SHapley Additive exPlanations) global summary plots to identify the …

cape-town Repository record for An analysis of the performance and interpretability of machine learning classification algorithms to predict long-term share returns on the JSE (opens in a new tab)

Design of a Machine Learning-based classifier for enhancing the accuracy and applicability of DAES, a novel autism screening tool [Sviluppo di un classificatore basato sul Machine Learning per migliorare l'accuratezza e l’applicabilità del DAES, un nuovo strumento di screening per l’autismo]

CIRNIGLIARO, LARAUniversità degli studi di Catania2026

… cinque algoritmi di ML (Random Forest – RF, Support Vector Classifier – SVC, Decision Tree – DT, Regressione Logistica – LR, e K-Nearest Neighbors – KNN) per classificare i bambini a rischio di ASD rispetto a quelli con DD e TD, nelle due differenti fasce d’età. RF e SVC sono risultati i …

catania Repository record for Design of a Machine Learning-based classifier for enhancing the accuracy and applicability of DAES, a novel autism screening tool [Sviluppo di un classificatore basato sul Machine Learning per migliorare l'accuratezza e l’applicabilità del DAES, un nuovo strumento di screening per l’autismo] (opens in a new tab)

Multi-function RF for Situational Awareness

Liu, Yang

… a two-stage solution for motion detection using support vector machines (SVM). A one-class SVM model is first evaluated whose training data are from human free environment only. Decontamination of human presence data using the one-class SVM is done prior to motion detection through a two-class …

syracuse-diss Repository record for Multi-function RF for Situational Awareness (opens in a new tab)

Machine and Deep Learning Approach for Type 2 Diabetes Prediction Using the CDC’s BRFSS Dataset: A Retrospective Analysis

Mpanga, Justin NgoyiUniversity of Missouri--Kansas City2022

… (ML) and neural network or multilayer perceptron classifier (NN) model(s) and test their performance on predicting the risk for T2DM. A copy of the dataset was transformed to have balanced classes in the outcome variable to allow further comparison of performance for each predictive model when …

umkc Repository record for Machine and Deep Learning Approach for Type 2 Diabetes Prediction Using the CDC’s BRFSS Dataset: A Retrospective Analysis (opens in a new tab)

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