Kooperativer Bibliotheksverbund

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Format: 1 online resource (452 pages)

Edition: 1st ed.

ISBN: 9781784392048

Content: About This BookGain insight into how data scientists collect, process, analyze, and visualize data using some of the most popular R packagesUnderstand how to apply useful data analysis techniques in R for real-world applicationsAn easy-to-follow guide to make the life of data scientist easier with the problems faced while performing data analysisWho This Book Is For R for Data Science Cookbook is intended for those who are already familiar with the basic operation of R, but want to learn how to efficiently and effectively analyze real-world data problems using practical R packages. What You Will LearnGet to know the functional characteristics of the R languageExtract, transform, and load data from heterogeneous sourcesUnderstand how easily R can confront probability and statistics problemsGet simple R instructions to quickly organize and manipulate large datasetsCreate professional data visualizations and interactive reportsPredict user purchase behavior by adopting a classification approachImplement data mining techniques to discover items that are frequently purchased togetherIn Detail This cookbook offers a range of data analysis samples in simple and straightforward R code, providing step-by-step resources and time-saving methods to help you solve data problems efficiently. The first section deals with how to create R functions to avoid the unnecessary duplication of code. You will learn how to prepare, process, and perform sophisticated ETL for heterogeneous data sources with R packages. Later chapters offer insight into time series analysis on financial data, while there is detailed information on the hot topic of machine learning, including data classification, regression, and so on. By the end of this book, you will understand how to resolve issues and will be able to comfortably offer solutions to problems encountered while performing

Content: data analysis

Note: Cover -- Copyright -- Credits -- About the Author -- About the Reviewer -- www.PacktPub.com -- Table of Contents -- Preface -- Chapter 1: Functions in R -- Introduction -- Creating R functions -- Matching arguments -- Understanding environments -- Working with lexical scoping -- Understanding closure -- Performing lazy evaluation -- Creating infix operators -- Using the replacement function -- Handling errors in a function -- The debugging function -- Chapter 2: Data Extracting, Transforming, and Loading -- Introduction -- Downloading open data -- Reading and writing CSV files -- Scanning text files -- Working with Excel files -- Reading data from databases -- Scraping web data -- Accessing Facebook data -- Working with twitteR -- Chapter 3: Data Preprocessing and Preparation -- Introduction -- Renaming the data variable -- Converting data types -- Working with the date format -- Adding new records -- Filtering data -- Dropping data -- Merging data -- Sorting data -- Reshaping data -- Detecting missing data -- Imputing missing data -- Chapter 4: Data Manipulation -- Introduction -- Enhancing a data.frame with a data.table -- Managing data with a data.table -- Performing fast aggregation with a data.table -- Merging large datasets with a data.table -- Subsetting and slicing data with dplyr -- Sampling data with dplyr -- Selecting columns with dplyr -- Chaining operations in dplyr -- Arranging rows with dplyr -- Eliminating duplicated rows with dplyr -- Adding new columns with dplyr -- Summarizing data with dplyr -- Merging data with dplyr -- Chapter 5: Visualizing Data with ggplot2 -- Introduction -- Creating basic plots with ggplot2 -- Changing aesthetics mapping -- Introducing geometric objects -- Performing transformations -- Adjusting scales -- Faceting -- Adjusting themes -- Combining plots -- Creating maps , Chapter 6: Making Interactive Reports -- Introduction -- Creating R Markdown reports -- Learning the markdown syntax -- Embedding R code chunks -- Creating interactive graphics with ggvis -- Understanding basic syntax and grammar -- Controlling axes and legends -- Using scales -- Adding interactivity to a ggvis plot -- Creating an R Shiny document -- Publishing an R Shiny report -- Chapter 7: Simulation from Probability Distributions -- Introduction -- Generating random samples -- Understanding uniform distributions -- Generating binomial random variates -- Generating Poisson random variates -- Sampling from a normal distribution -- Sampling from a chi-squared distribution -- Understanding Student's t-distribution -- Sampling from a dataset -- Simulating the stochastic process -- Chapter 8: Statistical Inference in R -- Introduction -- Getting confidence intervals -- Performing Z-tests -- Performing student's T-tests -- Conducting exact binomial tests -- Performing Kolmogorov-Smirnov tests -- Working with the Pearson's Chi-squared tests -- Understanding the Wilcoxon Rank Sum and Signed Rank tests -- Conducting one-way ANOVA -- Performing two-way ANOVA -- Chapter 9: Rule and Pattern Mining with R -- Introduction -- Transforming data into transactions -- Displaying transactions and associations -- Mining associations with the Apriori rule -- Pruning redundant rules -- Visualizing association rules -- Mining frequent itemsets with Eclat -- Creating transactions with temporal information -- Mining frequent sequential patterns with cSPADE -- Chapter 10: Time Series Mining with R -- Introduction -- Creating time series data -- Plotting a time series object -- Decomposing time series -- Smoothing time series -- Forecasting time series -- Selecting an ARIMA model -- Creating an ARIMA model -- Forecasting with an ARIMA model , Predicting stock prices with an ARIMA model -- Chapter 11: Supervised Machine Learning -- Introduction -- Fitting a linear regression model with lm -- Summarizing linear model fits -- Using linear regression to predict unknown values -- Measuring the performance of the regression model -- Performing a multiple regression analysis -- Selecting the best-fitted regression model with stepwise regression -- Applying the Gaussian model for generalized linear regression -- Performing a logistic regression analysis -- Building a classification model with recursive partitioning trees -- Visualizing a recursive partitioning tree -- Measuring model performance with a confusion matrix -- Measuring prediction performance using ROCR -- Chapter 12: Unsupervised Machine Learning -- Introduction -- Clustering data with hierarchical clustering -- Cutting tree into clusters -- Clustering data with the k-means method -- Clustering data with the density-based method -- Extracting silhouette information from clustering -- Comparing clustering methods -- Recognizing digits using the density-based clustering method -- Grouping similar text documents with k-means clustering methods -- Performing dimension reduction with Principal Component Analysis (PCA) -- Determining the number of principal components using a scree plot -- Determining the number of principal components using the Kaiser method -- Visualizing multivariate data using a biplot -- Index

Additional Edition: Print version Chiu), Yu-Wei, Chiu (David R for Data Science Cookbook Birmingham : Packt Publishing, Limited,c2016

Language: English

Keywords: Electronic books ; Electronic books

URL: FULL  ((OIS Credentials Required))

URL: FULL  ((OIS Credentials Required))

UID:

Format: 1 online resource (452 pages) : , color illustrations.

Edition: 1st edition

ISBN: 1-78439-204-9

Series Statement: Quick answers to common problems

Content: Over 100 hands-on recipes to effectively solve real-world data problems using the most popular R packages and techniques About This Book Gain insight into how data scientists collect, process, analyze, and visualize data using some of the most popular R packages Understand how to apply useful data analysis techniques in R for real-world applications An easy-to-follow guide to make the life of data scientist easier with the problems faced while performing data analysis Who This Book Is For This book is for those who are already familiar with the basic operation of R, but want to learn how to efficiently and effectively analyze real-world data problems using practical R packages. What You Will Learn Get to know the functional characteristics of R language Extract, transform, and load data from heterogeneous sources Understand how easily R can confront probability and statistics problems Get simple R instructions to quickly organize and manipulate large datasets Create professional data visualizations and interactive reports Predict user purchase behavior by adopting a classification approach Implement data mining techniques to discover items that are frequently purchased together Group similar text documents by using various clustering methods In Detail This cookbook offers a range of data analysis samples in simple and straightforward R code, providing step-by-step resources and time-saving methods to help you solve data problems efficiently. The first section deals with how to create R functions to avoid the unnecessary duplication of code. You will learn how to prepare, process, and perform sophisticated ETL for heterogeneous data sources with R packages. An example of data manipulation is provided, illustrating how to use the ?dplyr? and ?data.table? packages to efficiently process larger data structures. We also focus on ?ggplot2? and show you how to create advanced figures for data exploration. In addition, you will learn how to build an interactive report using the ?ggvis? package. Later chapters offer insight into time series analysis on financial data, while there is detailed information on the hot topic of machine learning, including data classification, regression, clustering, association rule mining, and dimension reduction. By the end of this book, you will understand how to resolve issues and will be able to comfortably offer solutions to problems encountered while performing data analysis. Style and approach This easy-to-follow gu...

Note: Includes index. , Cover -- Copyright -- Credits -- About the Author -- About the Reviewer -- www.PacktPub.com -- Table of Contents -- Preface -- Chapter 1: Functions in R -- Introduction -- Creating R functions -- Matching arguments -- Understanding environments -- Working with lexical scoping -- Understanding closure -- Performing lazy evaluation -- Creating infix operators -- Using the replacement function -- Handling errors in a function -- The debugging function -- Chapter 2: Data Extracting, Transforming, and Loading -- Introduction -- Downloading open data -- Reading and writing CSV files -- Scanning text files -- Working with Excel files -- Reading data from databases -- Scraping web data -- Accessing Facebook data -- Working with twitteR -- Chapter 3: Data Preprocessing and Preparation -- Introduction -- Renaming the data variable -- Converting data types -- Working with the date format -- Adding new records -- Filtering data -- Dropping data -- Merging data -- Sorting data -- Reshaping data -- Detecting missing data -- Imputing missing data -- Chapter 4: Data Manipulation -- Introduction -- Enhancing a data.frame with a data.table -- Managing data with a data.table -- Performing fast aggregation with a data.table -- Merging large datasets with a data.table -- Subsetting and slicing data with dplyr -- Sampling data with dplyr -- Selecting columns with dplyr -- Chaining operations in dplyr -- Arranging rows with dplyr -- Eliminating duplicated rows with dplyr -- Adding new columns with dplyr -- Summarizing data with dplyr -- Merging data with dplyr -- Chapter 5: Visualizing Data with ggplot2 -- Introduction -- Creating basic plots with ggplot2 -- Changing aesthetics mapping -- Introducing geometric objects -- Performing transformations -- Adjusting scales -- Faceting -- Adjusting themes -- Combining plots -- Creating maps. , Chapter 6: Making Interactive Reports -- Introduction -- Creating R Markdown reports -- Learning the markdown syntax -- Embedding R code chunks -- Creating interactive graphics with ggvis -- Understanding basic syntax and grammar -- Controlling axes and legends -- Using scales -- Adding interactivity to a ggvis plot -- Creating an R Shiny document -- Publishing an R Shiny report -- Chapter 7: Simulation from Probability Distributions -- Introduction -- Generating random samples -- Understanding uniform distributions -- Generating binomial random variates -- Generating Poisson random variates -- Sampling from a normal distribution -- Sampling from a chi-squared distribution -- Understanding Student's t-distribution -- Sampling from a dataset -- Simulating the stochastic process -- Chapter 8: Statistical Inference in R -- Introduction -- Getting confidence intervals -- Performing Z-tests -- Performing student's T-tests -- Conducting exact binomial tests -- Performing Kolmogorov-Smirnov tests -- Working with the Pearson's Chi-squared tests -- Understanding the Wilcoxon Rank Sum and Signed Rank tests -- Conducting one-way ANOVA -- Performing two-way ANOVA -- Chapter 9: Rule and Pattern Mining with R -- Introduction -- Transforming data into transactions -- Displaying transactions and associations -- Mining associations with the Apriori rule -- Pruning redundant rules -- Visualizing association rules -- Mining frequent itemsets with Eclat -- Creating transactions with temporal information -- Mining frequent sequential patterns with cSPADE -- Chapter 10: Time Series Mining with R -- Introduction -- Creating time series data -- Plotting a time series object -- Decomposing time series -- Smoothing time series -- Forecasting time series -- Selecting an ARIMA model -- Creating an ARIMA model -- Forecasting with an ARIMA model. , Predicting stock prices with an ARIMA model -- Chapter 11: Supervised Machine Learning -- Introduction -- Fitting a linear regression model with lm -- Summarizing linear model fits -- Using linear regression to predict unknown values -- Measuring the performance of the regression model -- Performing a multiple regression analysis -- Selecting the best-fitted regression model with stepwise regression -- Applying the Gaussian model for generalized linear regression -- Performing a logistic regression analysis -- Building a classification model with recursive partitioning trees -- Visualizing a recursive partitioning tree -- Measuring model performance with a confusion matrix -- Measuring prediction performance using ROCR -- Chapter 12: Unsupervised Machine Learning -- Introduction -- Clustering data with hierarchical clustering -- Cutting tree into clusters -- Clustering data with the k-means method -- Clustering data with the density-based method -- Extracting silhouette information from clustering -- Comparing clustering methods -- Recognizing digits using the density-based clustering method -- Grouping similar text documents with k-means clustering methods -- Performing dimension reduction with Principal Component Analysis (PCA) -- Determining the number of principal components using a scree plot -- Determining the number of principal components using the Kaiser method -- Visualizing multivariate data using a biplot -- Index.

Additional Edition: ISBN 1-78439-081-X

Language: English

UID:

Format: 1 online resource (438 pages)

Edition: 1. Edition.

ISBN: 1-62623-518-X

Content: A reader-friendly, how-to guide on reconstructive plastic surgery from international experts Reconstructive Plastic Surgery: An Atlas of Essential Procedures edited by esteemed authors, educators, and surgeons Robert X. Murphy Jr. and Charles K. Herman is a comprehensive resource detailing head-to-toe surgical procedures for a broad range of conditions. The senior editors have more than 50 years of collective surgical experience and expertise training hundreds of medical students and plastic surgery residents. A distinguished and diverse group of contributors from more than 15 countries and five continents share clinical pearls throughout the book. Sixty-seven chapters organized in five sections start with head and neck chapters detailing cleft palate defects and repair, followed by functional rhinoplasty, neoplasms, and trauma. Section two encompasses breast reduction/reconstruction techniques and other breast deformities; and management of trunk ulcers, deep wounds, and defects. The hand and upper extremity section details reconstructive techniques for infections, trauma, and Dupuytren's contracture. The final two sections cover a wide spectrum of nerve-related conditions and syndromes, followed by burns, melanoma, and vascular anomalies. Key Features High-quality illustrations and intraoperative photographs enhance understanding of step-by-step operative procedures More than 30 procedural videos provide hands-on guidance on how to perform specific steps in reconstructive plastic surgery A broad range of reconstructive techniques cover trauma, tumor resection, burns, congenital deformities, and degenerative conditions Consistent chapter formatting includes a clear and concise introduction, discussion of pertinent anatomy, surgical indications, operative techniques, complications, and long-term results This highly accessible yet comprehensive

Content: procedural guide is must-have reading for medical students, plastic surgery residents, and early-career plastic surgeons. It will also benefit veteran reconstructive plastic surgeons looking for a robust refresher with an international perspective.

Note: Reconstructive Plastic Surgery: An Atlas of Essential Procedures -- MedOne Access Information -- Title Page -- Copyright -- Contents -- Videos -- Foreword -- Preface -- Acknowledgments -- Contributors -- Section I Head and Neck -- Subsection IA Congenital Defects -- 1 Primary/Secondary Cleft Palate Repair -- 2 Cleft Lip and Nose Repair -- 3 Velopharyngeal Insufficiency -- 4 Velopharyngeal Insufficiency: Pharyngoplasty -- 5 Cleft Lip Nasal Deformity Repair -- 6 Syndromic and Nonsyndromic Craniosynostosis: Surgery of the Vault -- 7 Ear Reconstruction -- 8 Otoplasty -- Subsection IB Functional Rhinoplasty -- 9 Open Rhinoplasty -- 10 Closed Rhinoplasty Techniques -- Subsection IC Neoplasms -- 11 Treatment of Skin Cancer of the Head and Neck -- 12 Reconstruction after Neoplasm Resection with Regional Flaps -- 13 Reconstruction after Head and Neck Neoplasm Resection with Free Flaps -- 14 Lip Reconstruction -- 15 Eyelid Reconstruction -- 16 Nasal Reconstruction -- 17 Cheek Reconstruction -- Subsection ID Trauma -- 18 Mandible Reconstruction -- 19 Upper Midface Trauma -- 20 Nasal Fracture -- 21 Treatment of Orbital Wall Fractures -- 22 Facial Paralysis -- Section II Breast -- Subsection IIA Macromastia -- 23 Breast Reduction in the Female Patient: General Considerations -- 24 Wise Pattern, Inferior Pedicle Reduction Mammoplasty -- 25 Vertical Scar Reduction Mammoplasty -- 26 Reduction of the Male and Transmale Breast -- Subsection IIB Absent Breast -- 27 Breast Reconstruction-General Considerations -- 28 Breast Reconstruction with Implants or Tissue Expanders -- 29 Breast Reconstruction with Pedicled Latissimus Dorsi Flap -- 30 Breast Reconstruction with Pedicled Transverse Rectus Abdominis Flap -- 31 Breast Reconstruction with Free Transverse Rectus Abdominis Muscle Flap -- 32 Breast Reconstruction with Free Perforator Flaps. , 33 Secondary Procedures of the Reconstructed Breast -- Subsection IIC Other Deformities of Breast -- 34 Tuberous Breast Deformity -- 35 Poland's Syndrome -- Subsection IID Trunk -- 36 Treatment of Pressure Ulcers -- 37 Treatment of Pressure Ulcers with Flaps -- 38 Management of Deep Sternal Wound Infections -- 39 Reconstruction of Thoracic and Abdominal Defects -- 40 Vascularized Lymph Node Transfer -- Section III Hand and Upper Extremity -- 41 Hand Infections -- 42 Fingertip and Nail Bed Injuries -- 43 Local Flaps for Finger and Hand Reconstruction -- 44 Extensor Tendon Injuries and Repair -- 45 Flexor Tendon Repair -- 46 Tendon Transfers -- 47 Nerve Repair -- 48 Hand Fractures/Dislocations -- 49 Dupuytren's Contracture -- Section IV Nerve Compression -- 50 Median Nerve Compression -- 51 Ulnar Nerve Compression from Wrist to Elbow-Cubital Tunnel and Guyon's Canal Release -- 52 Pronator Syndrome -- 53 Radial Nerve Syndrome -- 54 Arterial Insufficiency, Reconstruction, and Amputation -- 55 Acute Compartment Syndrome -- 56 Arterial Repair, Revascularization, or Replantation of Digit, Hand, or Upper Extremity -- 57 Rheumatoid Hand -- 58 Articular Surgery for the Scleroderma Hand: Arthrodesis and Arthroplasty -- 59 Treatment of Degenerative Arthritis of the Wrist: Arthrodesis and Arthroplasty -- 60 Thumb Reconstruction: Toe-to-Thumb Transfer -- 61 Treatment of Tumors of the Hand: Sarcoma -- 62 Congenital Hand Reconstruction -- 63 Lower Extremity: Soft Tissue Reconstruction -- 64 Lower Extremity Wound Treatment with Free Flap -- Section V Integument -- 65 Burn Reconstruction -- 66 Lesions of the Integument: Treatment of Cancers of the Integument Including Malignant Melanoma -- 67 Vascular Anomalies and Congenital Nevi -- Index -- Additional MedOne Access Information.

Additional Edition: ISBN 1-62623-517-1

Language: English

Keywords: Atlas

DOI: 10.1055/b-006-163733

UID:

Format: iv, 32 pages : , digital, PDF file.

Series Statement: ARL-TR ; 4573

Note: Title from title screen (viewed June 15, 2009). , "September 2008." , Mode of access: Internet from the ARL web site. Address as of 6/15/09: http://www.arl.army.mil/arlreports/2008/ARL-TR-4573.pdf; current access available via PURL.

Language: English

UID:

Format: vi, 25 pages : , digital, PDF file.

Series Statement: ARL-TR ; 4322

Note: Title from title screen (viewed March 5, 2009). , "November 2007." , Mode of access: Internet from ARL web site. Address as of 3/05/2009: http://www.arl.army.mil/arlreports/2007/ARL-TR-4322.pdf; current access via PURL.

Language: English

UID:

Format: vi, 25 pages : , digital, PDF file.

Series Statement: ARL-TR ; 4322

Note: Title from title screen (viewed March 5, 2009). , "November 2007." , Mode of access: Internet from ARL web site. Address as of 3/05/2009: http://www.arl.army.mil/arlreports/2007/ARL-TR-4322.pdf; current access via PURL.

Language: English

UID:

Format: 1 online resource (vi, 42 pages) : , illustrations (some color).

Series Statement: ARL-TR ; 5713

Note: Title from title screen (viewed on Oct. 28, 2011). , "September 2011."

Language: English

UID:

Format: 1 online resource (vi, 42 pages) : , illustrations (some color).

Series Statement: ARL-TR ; 5713

Note: Title from title screen (viewed on Oct. 28, 2011). , "September 2011."

Language: English

UID:

Format: iv, 32 pages : , digital, PDF file.

Series Statement: ARL-TR ; 4573

Note: Title from title screen (viewed June 15, 2009). , "September 2008." , Mode of access: Internet from the ARL web site. Address as of 6/15/09: http://www.arl.army.mil/arlreports/2008/ARL-TR-4573.pdf; current access available via PURL.

Language: English