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 16 of 16 for “"k-fold cross validation"”.
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Empirical investigations of properties of robust aircraft routing models
… network and a 165-flight network. The K-fold cross validation approach is incorporated into aircraft routing problems to eliminate overfitting. According to the three evaluation metrics – on time performance, average total propagated delay and passenger disruptions, several good …
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A Machine Learning Approach to Network Intrusion Detection System Using K Nearest Neighbor and Random Forest
… research applies k nearest neighbours with 10-fold cross validation and random forest machine learning algorithms to a network-based intrusion detection system in order to improve the accuracy of the intrusion detection system. This project focused on specific feature selection improve the …
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Timing as a side-channel vulnerability: neural network analysis of generalized PIN prediction
… assesses whether these patterns generalize across users, testing a 10,000-class classification problem with out-of-sample k-fold cross-validation. Results show limited pattern detection—a top-1 accuracy of 0.115% and a top-10 of 1.198%, exceeding random guessing but insufficient for practical …
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Automated AI Classification of Midpalatal Suture Maturation Stages Using Deep Learning Framework
… (DCT) layers. Our method was validated with a k-fold cross validation protocol. The novel architecture demonstrated a classification accuracy of 79.02%, outperforming other methods and marking a substantial advancement in orthodontic diagnosis and treatment planning.
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Habitat Modeling of Three Endemic Crayfish Species in the Black River Drainage of Missouri and Arkansas: Factors Affecting Distribution and Abundance
… factors influence these three species across multiple spatial scales. Local and landscape data were used in decision tree analyses (CART) to determine their influence effect on presence/absence and density of the three species. Predictive models were validated using k-fold cross …
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DeepSampling: Image Sampling Technique for Cost-Effective Deep Learning
… in Deep Learning, choosing the right validation method is vital to ensure the accuracy and biases of the validation process. Current validation techniques, including k-fold cross-validation or random split of training and testing datasets, are hampered by the lack of systematic …
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Empirical study and business model analysis of successful freemium strategies in digital products
… and regression trees (CART) with k-fold cross validation is used to model on the training data and is validated on the test dataset to understand the influence of demographic, engagement, retention and social factors on subscribers. Five successful premium companies Linkedln, Zynga, …
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Closed-loop metrics-based dataset optimization toward deep learning models
… procedimentos de avaliação posteriores, como a K-Fold Cross Validation (KFCV) . Apesar da sua adoção generalizada, algumas limitações podem ser identificadas nestas práticas padronizadas. Por um lado, os procedimentos de divisão e aumento de conjuntos de dados são tipicamente realizados sem …
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Investigating Violation Behavior at Intersections using Intelligent Transportation Systems: A Feasibility Analysis on Vehicle/Bicycle-to-Infrastructure Communications as a Potential Countermeasure
… Intelligence techniques were adopted. K-fold Cross-Validation as well as Out-of-Bag error was used for model selection and validation. Transportation mode recognition models contributed to high classification accuracies (e.g., up to 98%). Thus, data obtained from the smartphone sensors …
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Registration of Tomographic Images to X-ray Projections for Use in Image Guided Interventions
… from aortic stenting procedures, where k-fold cross validation was<br/>used to obtain an estimate of the registration accuracy. The results from these experiments showed that two measures were able to<br/>register accurately (RMS rotational error of 0.76 degrees and RMS in-plane …
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From big data to personal narratives: a supervised learning framework for decoding the course of traumatic brain injury in intensive care
… to return probability estimates, calibrated on validation sets, at each threshold of the endpoint. Regularised model weights are trained through supervised learning, and the reliability and information content of the modelling strategy are evaluated with repeated k-fold cross validation. …
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Model Selection, Uniform Inference and Nonparametric Regression
… The first chapter is concerned with K-fold cross-validation and shows that the cross- validated least-squares estimator predicts the response equally well as the unfeasible best-linear predictor whose dimension may diverge with the sample size. This property, known as risk consistency, …
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Predicting Corn Response to Variable Synthetic Fertilizer Treatments Using UAV-Derived Imagery
… (P), and potassium (K) fertilizer treatments across different growth stages. Two field trials (NP and K) were conducted at two locations in Virginia, Kentland Farm in Blacksburg (Kentland), Valley and Ridge province, and the Northern Piedmont Center in Orange (Orange), Piedmont province. These …
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Application of data-driven technologies for asthma self-management
… 2.Also using the AMHS data, I conducted a cross-sectional study. I used unsupervised learning (k-means clustering) to identify patient clusters based on markers of asthma attack. I then applied supervised learning (LASSO) to identify the key risk factors associated with each patient …
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On-line Final Quality Prediction for Multiphase Batch Processes with Uneven Durations
… local predictive PLS models were built using k-fold cross validation (k=10) to determine the appropriate number of components retained. Only 3-5 latent components were needed to capture 66-88% of the variance in final quality. The overall performance of all three approaches was assessed on-line …
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Yield Curves and Macro Variables Interactions and Predictions
This research is based on the yield curves and five macro variables, namely equity indices, FX rates, central banks’ policy rates, inflation rates and the GDP growth rates, for nine different markets, from different geographical regions. Our aim was to identify common trends in yield curves and …