Quantifying Structure In Random Forests
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Quantifying Structure In Random Forests
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Author : Hannah Sutton
language : en
Publisher:
Release Date : 2022
Quantifying Structure In Random Forests written by Hannah Sutton and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.
Random forests are often regarded as black-box machine learning models. They are sufficiently complex that they are not easily interpretable. This fact has inspired a variety of research into improving the interpretability of random forests, which is the focus of this thesis; specifically, we wish to capture dissimilarities between random forest trees using several comparison functions on the decision trees that comprise the random forest, allowing the structure of the random forest to be quantified. These include a phylogenetic metric designed for transmission trees, as well as others we developed that involve the count and location of variables in each tree, as well as the depths of the trees. This allows us to visualise an underlying grouping of the trees using a heatmap and hierarchical clustering, and analyze the predictive accuracy of the decision tree clusters. Finally we propose a method for generating random decision trees, which we then use to generate synthetic data using a small set of trees. We use the random forest trained on this data to determine which comparison functions are statistically significant and contribute to the overall clustering. Additionally, we investigate whether or not the random forest is capable of recovering the original trees that the data was created from.
Hands On Machine Learning With R
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Author : Brad Boehmke
language : en
Publisher: CRC Press
Release Date : 2019-11-07
Hands On Machine Learning With R written by Brad Boehmke and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-07 with Business & Economics categories.
Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today’s most popular machine learning methods. This book serves as a practitioner’s guide to the machine learning process and is meant to help the reader learn to apply the machine learning stack within R, which includes using various R packages such as glmnet, h2o, ranger, xgboost, keras, and others to effectively model and gain insight from their data. The book favors a hands-on approach, providing an intuitive understanding of machine learning concepts through concrete examples and just a little bit of theory. Throughout this book, the reader will be exposed to the entire machine learning process including feature engineering, resampling, hyperparameter tuning, model evaluation, and interpretation. The reader will be exposed to powerful algorithms such as regularized regression, random forests, gradient boosting machines, deep learning, generalized low rank models, and more! By favoring a hands-on approach and using real word data, the reader will gain an intuitive understanding of the architectures and engines that drive these algorithms and packages, understand when and how to tune the various hyperparameters, and be able to interpret model results. By the end of this book, the reader should have a firm grasp of R’s machine learning stack and be able to implement a systematic approach for producing high quality modeling results. Features: · Offers a practical and applied introduction to the most popular machine learning methods. · Topics covered include feature engineering, resampling, deep learning and more. · Uses a hands-on approach and real world data.
Computational Genomics With R
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Author : Altuna Akalin
language : en
Publisher: CRC Press
Release Date : 2020-12-16
Computational Genomics With R written by Altuna Akalin and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-16 with Mathematics categories.
Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.
Forest Mensuration
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Author : Anthonie van Laar
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-07-20
Forest Mensuration written by Anthonie van Laar and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-07-20 with Technology & Engineering categories.
Van Laar and Akça’s popular text book, Forest Mensuration, was first published in 1997. Like that first edition, this modern update is based on extensive research, teaching and practical experience in both Europe, and the tropics and subtropics. However, it has also been extensively revised, and now includes chapters on remote sensing and the application of aerial photographs and satellite imagery. The book assumes no advanced knowledge of statistical methods, and combines practical techniques with important historical and disciplinary context. The result is a strong balance between a handbook and a valuable reference.
Parameter Estimation And Uncertainty Quantification In Water Resources Modeling
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Author : Philippe Renard
language : en
Publisher: Frontiers Media SA
Release Date : 2020-04-22
Parameter Estimation And Uncertainty Quantification In Water Resources Modeling written by Philippe Renard and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-22 with categories.
Numerical models of flow and transport processes are heavily employed in the fields of surface, soil, and groundwater hydrology. They are used to interpret field observations, analyze complex and coupled processes, or to support decision making related to large societal issues such as the water-energy nexus or sustainable water management and food production. Parameter estimation and uncertainty quantification are two key features of modern science-based predictions. When applied to water resources, these tasks must cope with many degrees of freedom and large datasets. Both are challenging and require novel theoretical and computational approaches to handle complex models with large number of unknown parameters.
Quantifying Uncertainty In Subsurface Systems
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Author : Céline Scheidt
language : en
Publisher: John Wiley & Sons
Release Date : 2018-06-19
Quantifying Uncertainty In Subsurface Systems written by Céline Scheidt and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-19 with Science categories.
Under the Earth's surface is a rich array of geological resources, many with potential use to humankind. However, extracting and harnessing them comes with enormous uncertainties, high costs, and considerable risks. The valuation of subsurface resources involves assessing discordant factors to produce a decision model that is functional and sustainable. This volume provides real-world examples relating to oilfields, geothermal systems, contaminated sites, and aquifer recharge. Volume highlights include: A multi-disciplinary treatment of uncertainty quantification Case studies with actual data that will appeal to methodology developers A Bayesian evidential learning framework that reduces computation and modeling time Quantifying Uncertainty in Subsurface Systems is a multidisciplinary volume that brings together five major fields: information science, decision science, geosciences, data science and computer science. It will appeal to both students and practitioners, and be a valuable resource for geoscientists, engineers and applied mathematicians. Read the Editors' Vox: eos.org/editors-vox/quantifying-uncertainty-about-earths-resources
Percent Canopy Cover And Stand Structure Statistics From The Forest Vegetation Simulator
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Author : Nicholas L. Crookston
language : en
Publisher:
Release Date : 1999
Percent Canopy Cover And Stand Structure Statistics From The Forest Vegetation Simulator written by Nicholas L. Crookston and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Forest canopies categories.
Multiscale Modeling And Uncertainty Quantification Of Materials And Structures
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Author : Manolis Papadrakakis
language : en
Publisher: Springer
Release Date : 2014-07-02
Multiscale Modeling And Uncertainty Quantification Of Materials And Structures written by Manolis Papadrakakis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-02 with Science categories.
This book contains the proceedings of the IUTAM Symposium on Multiscale Modeling and Uncertainty Quantification of Materials and Structures that was held at Santorini, Greece, September 9 – 11, 2013. It consists of 20 chapters which are divided in five thematic topics: Damage and fracture, homogenization, inverse problems–identification, multiscale stochastic mechanics and stochastic dynamics. Over the last few years, the intense research activity at micro scale and nano scale reflected the need to account for disparate levels of uncertainty from various sources and across scales. As even over-refined deterministic approaches are not able to account for this issue, an efficient blending of stochastic and multiscale methodologies is required to provide a rational framework for the analysis and design of materials and structures. The purpose of this IUTAM Symposium was to promote achievements in uncertainty quantification combined with multiscale modeling and to encourage research and development in this growing field with the aim of improving the safety and reliability of engineered materials and structures. Special emphasis was placed on multiscale material modeling and simulation as well as on the multiscale analysis and uncertainty quantification of fracture mechanics of heterogeneous media. The homogenization of two-phase random media was also thoroughly examined in several presentations. Various topics of multiscale stochastic mechanics, such as identification of material models, scale coupling, modeling of random microstructures, analysis of CNT-reinforced composites and stochastic finite elements, have been analyzed and discussed. A large number of papers were finally devoted to innovative methods in stochastic dynamics.
Quantifying Error In Vegetation Mapping
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Author : Erica Serna
language : en
Publisher:
Release Date : 2011
Quantifying Error In Vegetation Mapping written by Erica Serna and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Electronic dissertations categories.
Understanding the current distribution and structure of forest vegetation is important for designing forest management plans and prioritizing restoration at landscape scales. This project provides information on Random Forest, a relatively new statistical package in the field of forestry, and patterns in mapping errors, a less explored field of study particularly in the forests of the Midwest United States. Vegetation maps can be made from classification and regression trees, such as Random Forest, by integrating environmental variables with vegetation information. An understanding of the accuracy of the maps is important because management plans and restoration efforts are more effective with accurate data. This study was done in forested regions in Minnesota with the purpose of 1) analyzing physiographic factors controlling tree species distribution; 2) mapping potential species distributions; 3) quantifying error in vegetation mapping; and 4) understanding map accuracy by evaluating minimum amounts of sample data necessary for reliable mapping. The results from Random Forest were found to be realistic ecologically and biologically. Also, tree species required records of 1-2 trees per 10,000 ha to produce accurate maps. Knowing the minimum amount of data points necessary for acceptable accuracy assists scientists mapping vegetation. This study demonstrates the effectiveness of Random Forest in vegetation mapping, which can be useful for future vegetation mapping.
Growth And Ecosystem Services Of Urban Trees
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Author : Thomas Rötzer
language : en
Publisher: MDPI
Release Date : 2019-10-23
Growth And Ecosystem Services Of Urban Trees written by Thomas Rötzer and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-23 with Science categories.
Numerous studies indicate an accelerated growth of forest trees, induced by ongoing climate change. Similar trends were recently found for urban trees in major cities worldwide. Studies frequently report about substantial effects of climate change and the urban heat island effect (UHI) on plant growth. The combined effects of increasing temperatures, changing precipitation patterns, and extended growing season lengths, in addition to increasing nitrogen deposition and higher CO2 concentrations, can increase but also reduce plant growth. Closely related to this, the multiple functions and services provided by urban trees may be modified. Urban trees generate numerous ecosystem services, including carbon storage, mitigation of the heat island effect, reduction of rainwater runoff, pollutant filtering, recreation effects, shading, and cooling. The quantity of the ecosystem services is often closely associated with the species, structure, age, and size of the tree as well as with a tree’s vitality. Therefore, greening cities, and particularly planting trees, seems to be an effective option to mitigate climate change and the UHI. The focus of this Special Issue is to underline the importance of trees as part of the urban green areas for major cities in all climate zones. Empirical as well as modeling studies of urban tree growth and their services and disservices in cities worldwide are included. Articles about the dynamics, structures, and functions of urban trees as well as the influence of climate and climate change on urban tree growth, urban species composition, carbon storage, and biodiversity are also discussed.