Download or read book Random Trees written by Michael Drmota and published by Springer Science & Business Media. This book was released on 2009-04-16 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this book is to provide a thorough introduction to various aspects of trees in random settings and a systematic treatment of the mathematical analysis techniques involved. It should serve as a reference book as well as a basis for future research.
Download or read book Random Trees written by Michael Drmota and published by Springer. This book was released on 2009-08-29 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this book is to provide a thorough introduction to various aspects of trees in random settings and a systematic treatment of the mathematical analysis techniques involved. It should serve as a reference book as well as a basis for future research.
Download or read book Random Generation of Trees written by Laurent Alonso and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: Random Generation of Trees is about a field on the crossroads between computer science, combinatorics and probability theory. Computer scientists need random generators for performance analysis, simulation, image synthesis, etc. In this context random generation of trees is of particular interest. The algorithms presented here are efficient and easy to code. Some aspects of Horton--Strahler numbers, programs written in C and pictures are presented in the appendices. The complexity analysis is done rigorously both in the worst and average cases. Random Generation of Trees is intended for students in computer science and applied mathematics as well as researchers interested in random generation.
Download or read book Probability on Trees and Networks written by Russell Lyons and published by Cambridge University Press. This book was released on 2017-01-20 with total page 1106 pages. Available in PDF, EPUB and Kindle. Book excerpt: Starting around the late 1950s, several research communities began relating the geometry of graphs to stochastic processes on these graphs. This book, twenty years in the making, ties together research in the field, encompassing work on percolation, isoperimetric inequalities, eigenvalues, transition probabilities, and random walks. Written by two leading researchers, the text emphasizes intuition, while giving complete proofs and more than 850 exercises. Many recent developments, in which the authors have played a leading role, are discussed, including percolation on trees and Cayley graphs, uniform spanning forests, the mass-transport technique, and connections on random walks on graphs to embedding in Hilbert space. This state-of-the-art account of probability on networks will be indispensable for graduate students and researchers alike.
Download or read book Trees of North America and Europe written by Roger Phillips and published by New York : Random House. This book was released on 1978 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: This splendid guide to tree identification contains more than 1,000 full-color photographs. Each tree is illustrated in full detail -- by leaf, flower, fruit, bark, and mature tree shape -- and is fully described in the text. A unique leaf index makes the identification of trees simple and accurate. The trees are arranged alphabetically by Latin name and an index of common names concludes the book. An indispensable companion for both the enthusiast and the botanist.
Download or read book Random Forests with R written by Robin Genuer and published by Springer Nature. This book was released on 2020-09-10 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers an application-oriented guide to random forests: a statistical learning method extensively used in many fields of application, thanks to its excellent predictive performance, but also to its flexibility, which places few restrictions on the nature of the data used. Indeed, random forests can be adapted to both supervised classification problems and regression problems. In addition, they allow us to consider qualitative and quantitative explanatory variables together, without pre-processing. Moreover, they can be used to process standard data for which the number of observations is higher than the number of variables, while also performing very well in the high dimensional case, where the number of variables is quite large in comparison to the number of observations. Consequently, they are now among the preferred methods in the toolbox of statisticians and data scientists. The book is primarily intended for students in academic fields such as statistical education, but also for practitioners in statistics and machine learning. A scientific undergraduate degree is quite sufficient to take full advantage of the concepts, methods, and tools discussed. In terms of computer science skills, little background knowledge is required, though an introduction to the R language is recommended. Random forests are part of the family of tree-based methods; accordingly, after an introductory chapter, Chapter 2 presents CART trees. The next three chapters are devoted to random forests. They focus on their presentation (Chapter 3), on the variable importance tool (Chapter 4), and on the variable selection problem (Chapter 5), respectively. After discussing the concepts and methods, we illustrate their implementation on a running example. Then, various complements are provided before examining additional examples. Throughout the book, each result is given together with the code (in R) that can be used to reproduce it. Thus, the book offers readers essential information and concepts, together with examples and the software tools needed to analyse data using random forests.
Download or read book Computational Genomics with R written by Altuna Akalin and published by CRC Press. This book was released on 2020-12-16 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Decision Trees and Random Forests written by Mark Koning and published by Independently Published. This book was released on 2017-10-04 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you want to learn how decision trees and random forests work, plus create your own, this visual book is for you. The fact is, decision tree and random forest algorithms are powerful and likely touch your life everyday. From online search to product development and credit scoring, both types of algorithms are at work behind the scenes in many modern applications and services. They are also used in countless industries such as medicine, manufacturing and finance to help companies make better decisions and reduce risk. Whether coded or scratched out by hand, both algorithms are powerful tools that can make a significant impact. This book is a visual introduction for beginners that unpacks the fundamentals of decision trees and random forests. If you want to dig into the basics with a visual twist plus create your own algorithms in Python, this book is for you.
Download or read book Multiple Classifier Systems written by Josef Kittler and published by Springer. This book was released on 2003-05-15 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Driven by the requirements of a large number of practical and commercially - portant applications, the last decade has witnessed considerable advances in p- tern recognition. Better understanding of the design issues and new paradigms, such as the Support Vector Machine, have contributed to the development of - proved methods of pattern classi cation. However, while any performance gains are welcome, and often extremely signi cant from the practical point of view, it is increasingly more challenging to reach the point of perfection as de ned by the theoretical optimality of decision making in a given decision framework. The asymptoticity of gains that can be made for a single classi er is a re?- tion of the fact that any particular design, regardless of how good it is, simply provides just one estimate of the optimal decision rule. This observation has motivated the recent interest in Multiple Classi er Systems , which aim to make use of several designs jointly to obtain a better estimate of the optimal decision boundary and thus improve the system performance. This volume contains the proceedings of the international workshop on Multiple Classi er Systems held at Robinson College, Cambridge, United Kingdom (July 2{4, 2001), which was organized to provide a forum for researchers in this subject area to exchange views and report their latest results.
Download or read book Evolution of Random Search Trees written by Hosam M. Mahmoud and published by Wiley-Interscience. This book was released on 1992 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: While several excellent books have been written on algorithms and their analysis, remarkably few have been dedicated to the probabilistic analysis of algorithms. This graduate text/professional reference fills that gap and brings together material that is scattered over tens of publications. Its unifying theme is the study of some classes of random search trees suitable for use as data structures with a behavior of random growth that is almost as good as balanced trees.
Download or read book Probability and Real Trees written by Steven N. Evans and published by Springer. This book was released on 2007-09-26 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: Random trees and tree-valued stochastic processes are of particular importance in many fields. Using the framework of abstract "tree-like" metric spaces and ideas from metric geometry, Evans and his collaborators have recently pioneered an approach to studying the asymptotic behavior of such objects when the number of vertices goes to infinity. This publication surveys the relevant mathematical background and present some selected applications of the theory.
Download or read book Clusters Orders and Trees Methods and Applications written by Fuad Aleskerov and published by Springer. This book was released on 2014-06-11 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: The volume is dedicated to Boris Mirkin on the occasion of his 70th birthday. In addition to his startling PhD results in abstract automata theory, Mirkin’s ground breaking contributions in various fields of decision making and data analysis have marked the fourth quarter of the 20th century and beyond. Mirkin has done pioneering work in group choice, clustering, data mining and knowledge discovery aimed at finding and describing non-trivial or hidden structures—first of all, clusters, orderings and hierarchies—in multivariate and/or network data. This volume contains a collection of papers reflecting recent developments rooted in Mirkin’s fundamental contribution to the state-of-the-art in group choice, ordering, clustering, data mining and knowledge discovery. Researchers, students and software engineers will benefit from new knowledge discovery techniques and application directions.
Download or read book One Million Trees written by Kristen Balouch and published by Holiday House. This book was released on 2022-03-01 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: The real-life story of a family who planted 1,000,000 trees—yes, it’s true!—to fight deforestation in British Columbia. When Kristen Balouch was 10 years old, her parents made a surprising announcement: their whole family was going on a trip to plant trees! Kristen, her sisters, and her mom and dad—and their pet, Wonder Dog!—flew from their California home to a logging site in British Columbia. There, they joined a crew working to replant the trees that had been cut down. In One Million Trees, Kristen reflects on the forty days they spent living in a tent, covered in mud and bug bites, working hard every day to plant a new forest. Young readers will learn a little French, practice some math skills, and learn all about how to plant a tree the right way! The kid-friendly, engaging text is paired with bold illustrations, full of fun details and bright colors. The story ends with a modern-day look at what Kristen's family helped accomplish: a stand of huge trees growing on what used to be an empty, muddy patch of bare stumps. An author's note shares more information on deforestation, sustainable logging practices, and the irreplaceable environmental benefit of old growth forests. . . . Plus, the amazing things even a small group of people can do when they work together. A fun story with an important environmental message, One Million Trees is bound to inspire kids to get their hands dirty to make our planet healthy! A School Library Journal Best Book of the Year A Junior Library Guild Gold Standard Selection
Download or read book Tangled Trees written by Roderic D. M. Page and published by University of Chicago Press. This book was released on 2003 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, the use of molecular data to build phylogenetic trees and sophisticated computer-aided techniques to analyze them have led to a revolution in the study of cospeciation. Tangled Trees provides an up-to-date review and synthesis of current knowledge about phylogeny, cospeciation, and coevolution. The opening chapters present various methodological and theoretical approaches, ranging from the well-known parsimony approach to "jungles" and Bayesian statistical models. Then a series of empirical chapters discusses detailed studies of cospeciation involving vertebrate hosts and their parasites, including nematodes, viruses, and lice. Tangled Trees will be welcomed by researchers in a wide variety of fields, from parasitology and ecology to systematics and evolutionary biology. Contributors: Sarah Al-Tamimi, Michael A. Charleston, Dale H. Clayton, James W. Demastes, Russell D. Gray, Mark S. Hafner, John P. Huelsenbeck, J.-P. Hugot, Kevin P. Johnson, Peter Kabat, Bret Larget, Joanne Martin, Yannis Michalakis, Roderic D. M. Page, Ricardo L. Palma, Adrian M. Paterson, Susan L. Perkins, Andy Purvis, Bruce Rannala, David L. Reed, Fredrik Ronquist, Theresa A. Spradling, Jason Taylor, Michael Tristem
Download or read book Trees written by Brigitte Chauvin and published by Birkhäuser. This book was released on 2012-12-06 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: For the first time, the very different aspects of trees are presented here in one volume. Articles by specialists working in different areas of mathematics cover disordered systems, algorithms, probability, and p-adic analysis. Researchers and graduate students alike will benefit from the clear expositions.
Download or read book Hands On Machine Learning with R written by Brad Boehmke and published by CRC Press. This book was released on 2019-11-07 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Genetic Gains Through Testing and Crossing Longleaf Pine Plus Trees written by Calvin F. Bey and published by . This book was released on 1978 with total page 6 pages. Available in PDF, EPUB and Kindle. Book excerpt:
