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 “"Tree-based methods"”.
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Topics in Tree-Based Methods
This work introduces methods and associated software for enhancing the interpretability of fitted models, with emphasis on classification and regression trees. We begin in Chapter 1 by describing novel techniques for growing classification and regression trees designed to induce visually …
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Tree-based Methods for Learning Probability Distributions
… and mainly discussed herein are two types of new tree-based methods: a single-tree method and an ensemble method. The new single tree method, the main topic of Chapter 2, is introduced by constructing a generalized Polya tree process, that is, a new Bayesian nonparametric model, equipped with a …
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Advances in Bayesian Hierarchical Modeling with Tree-based Methods
… especially suitable for this task is the P\'olya tree type models. Following a divide-and-conquer strategy, these tree-based methods transform the original task into a series of tasks that are smaller in size and easier to solve while their nonparametric nature guarantees the modeling flexibility …
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Essays on Tree-based Methods for Prediction and Causal Inference
… chapter explores new variations of Bayesian tree-based machine learning algorithms. Bayesian Additive Regression Trees (BART) (Chipman et al. 2010) and Bayesian Causal Forests (BCF) (Hahn et al. 2020) are state-of-the-art machine learning methods for prediction and causal inference. A number …
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High-dimensional classification and attribute-based forecasting
… setting causes most existing classification methods, including penalized logistic regression, not appropriate to be directly applied because the assumption of independent observations is violated. To solve this problem, we propose a new classification method by incorporating random effects …
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Comparison of growth curve models for assessing height in a South African birth cohort
… results were compared to a random forest model. Methods for variable importance in classification problems using tree-based methods were explored. The random forest model appeared to perform similarly to the logistic regression model in terms of predictive power and variable interpretation. This …
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Optimal survival trees ensemble
Selection of accurate and diverse trees based on individual and collective performance in an ensemble has recently been studied for classification and regression problems. Following this notion, the possibility of selecting optimal survival trees is considered in this work. Initially, a large set …
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A Data-Driven Approach to Understanding the Attrition of Women in Software Engineering
… predictive models (using logistic regression and tree-based methods) were needed to illuminate factors that were not explicitly identified by respondents. The predictive models identified the primary reasons women leave SWE roles by comparing women who planned to remain in the SWE career path and …
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Applications of DNA-barcoding in the identification and understanding of grass invasions in Southern Africa
… for identification efficacy using three distance-based metrics and one tree-based metric in the R package SPIDER, both including and excluding singleton data. This study lists 128 naturalised grass species and subspecies found in South Africa. In the DNA barcoding analyses, matK was found to …
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EVALUATION AND MODELING OF RISK FACTORS ASSOCIATED WITH MICROBIAL CONTAMINATION IN PRODUCE PRE-HARVEST ENVIRONMENT
… farm were analyzed using logistic regression and tree-based methods. The developed models have robust predictive ability and can be used to estimate the risk of microbial contamination in mixed farms under different weather conditions. Survival and persistence of pathogens in field soil is a food …
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Machine Learning for Credit Default Risk
… out-of-sample implementations also suggest that tree-based methods may enable "shadow" sovereign CDS pricing for countries and periods in which reliable sovereign CDS data might not be available. In the second essay, we utilise a unique peer-to-peer (P2P) loan dataset to compare different machine …
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Ensemble Tree-Based Machine Learning for Imaging Data
… dissertation, we are proposing novel statistical tree-based methods with more efficient and more accurate responses for use in medical imaging applications.</p> <p>In Chapter 2, we introduce a gradient Boosted Trees for Spatial Data (Boost-S) with covariate information.The main innovation of this …
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Large Scale Nearest Neighbor Search - Theories, Algorithms, and Applications
… for lots of applications including content based search/retrieval, recommendation, clustering, graph and social network research, as well as many other machine learning and data mining problems. Exhaustive search is the simplest and most straightforward way for nearest neighbor search, but …
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Index analysis of semistate systems without passivity restrictions
… been an increasing interest on semistate models based on differential-algebraic equations (DAEs) for the analysis and simulation of non-linear electrical circuits. Modelling techniques such as Node Tableau Analysis (NTA), Augmented Nodal Analysis (ANA), or Modified Nodal Analysis (MNA), the …