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 14 of 14 for “"Boosted Decision Tree"”.
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Gradient Boosted Decision Tree Application to Muon Identification in the KLM at Belle II
We present the results of applying a Fast Boosted Decision Tree (FBDT) algorithm to the task of distinguishing muons from pions in K-Long and Muon (KLM) detector of the Belle II experiment. Performance was evaluated over a momentum range of 0.6 < p < 5.0 GeV/c by plotting Receiver Operating …
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A search for the ttH (H → bb) channel at the Large Hadron Collider with the ATLAS detector using a matrix element method
… analyses utilizing Neural Networks and Boosted Decision Trees respectively. As no significant excess is found, an observed (expected) limit of 3.4 (2.2) times the Standard Model cross-section is determined at 95% confidence, using the CLs method, for the Neural Network analysis. For the …
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Exclusive search for Higgs boson to gamma-gamma decay via vector boson fusion production mechanism
… limit to ~ 6[sigma]SM in this range by using a boosted decision tree. Comparison to the cut based approach used by the CMS Collaboration shows no improvement in using a BDT as opposed to a cut based approach.
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Searches for New Physics at the Large Hadron Collider
… used as a powerful probe into this coupling. A boosted decision tree analysis is performed to fully optimize the extraction of the thj signal. It is found that the combined effect of introducing the angular variable to the analysis as well as the usage of the boosted decision tree algorithm …
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A time domain phonon pulse fitting analysis for the cryogenic dark matter search experiment
… using the Markov chain Monte Carlo method. A Boosted Decision Tree (BDT) was then used to analyze the parameters from the fits to determine how well the parameters could distinguish between event types such as nuclear versus electron recoil events, and surface versus bulk events. Cuts made on …
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Entropy-based machine learning algorithms applied to genomics and pattern recognition
… and overall accuracy. In this thesis, we present decision tree (DT) methods applied to DNA sequence analysis that result in highly interpretable and accurate predictions. We propose a boosted decision tree (BDT) model using the binary counts of important DNA motifs to predict the binding …
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Machine learning based searches for new physics at the ATLAS experiment
… chargino and the lightest neutralino. Using a boosted decision tree to perform multiclass classification, separate regions in phase space can be defined that are enriched in either signal or a certain background. These regions are used to search for the supersymmetric signals and for improving …
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A search for tWZ production in the trilepton channel using Run 2 data from the ATLAS experiment
… suppressed through the use of the Gradient Boosted Decision Tree (GBDT) machine learning algorithm. First, a hadronically-decaying W boson candidate was identified using a GBDT; this was used to suppress WZ background events. Then, an event-level GBDT was used to suppress all background …
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Bugs, Drugs and Data: Antibiotic Resistance, Prevalence and Prediction of Bug-Drug Mismatch using Electronic Health Records (EHR) Data
… lasso regularization, random forest, gradient boosted decision tree and deep neural network). The trends in resistance rates to clinically relevant antibiotics were influenced by age and care setting. BDM prevalence for several critically important antibiotics differed between children and …
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High-Throughput Phenotyping and Genomic Prediction in Multi-Environment Plant Breeding Field Trials
… environments more accurately than a gradient boosted decision tree, simple linear regression, and spatial models. Cross-environment prediction was conducted, and higher grain yield prediction accuracies were observed for LASSO regression models using image features (mean R2 = 0.34) than …
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Search for a diffuse astrophysical neutrino flux with KM3NeT/ARCA
… μηχανικής μάθησης βασισμέ- νου στον αλγόριθμο Boosted Decision Tree (BDT), με στόχο τη βελτιστοποίηση της διάκρισης μεταξύ σήματος και υποβάθρου. Δύο ανεξάρτητα μοντέλα BDT αναπτύχθηκαν και βελτιστοποιήθηκαν για την επιλογή ανερχόμενων και, για πρώτη φορά, κατερχόμενων συμβάντων, λαμβάνοντας …
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Deep Neural Network Classifiers in CMS Track Reconstruction and in the Search for the Charged Higgs Boson
… another machine learning algorithm known as the boosted decision tree. Here the first application of deep neural networks to the task is presented with the goal of both simplifying the upkeep of the classifier as well as improving the performance. In the second topic the application of deep …
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Canaries in the coal mine: Boosted machine learning for the classification of recessions in the eurozone business cycle
… and the eurozone business cycle using a gradient boosted decision tree-based machine learning framework. To facilitate this analysis, XGBoost was used to provide a gradient boosting framework. Using quarterly GDP values for all of the EA19 (with the exception of Ireland due to data availability), …
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Uncertainty-Based Methodology for the Development of Space Domain Awareness Architectures in Three-Body Regimes
… model. Of the models tested, the model based on boosted decision trees was found to have the best balance of speed and accuracy. This massive increase in computational efficiency enables designers to evaluate much larger volumes of design cases using the same hardware. The third identified …