A Beginner`s Guide to Using Open Access Data, Airyalat
Автор: Pawel Cichosz Название: Data Mining Algorithms: Explained Using R ISBN: 111833258X ISBN-13(EAN): 9781118332580 Издательство: Wiley Рейтинг: Цена: 9971.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Data Mining Algorithms is a practical, technically-oriented guide to data mining algorithms that covers the most important algorithms for building classification, regression, and clustering models, as well as techniques used for attribute selection and transformation, model quality evaluation, and creating model ensembles.
Автор: Linoff Gordon S. Название: Data Analysis Using SQL and Excel ISBN: 111902143X ISBN-13(EAN): 9781119021438 Издательство: Wiley Рейтинг: Цена: 6178.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A practical guide to data mining using SQL and Excel Data Analysis Using SQL and Excel, 2nd Edition shows you how to leverage the two most popular tools for data query and analysis SQL and Excel to perform sophisticated data analysis without the need for complex and expensive data mining tools.
Описание: Big Data Analytics Using Splunk is a hands-on book showing how to process and derive business value from big data in real time. Using Splunk, you can monitor data in real time, or mine your data after the fact.
Автор: Matthias Kaeding Название: Bayesian Analysis of Failure Time Data Using P-Splines ISBN: 3658083921 ISBN-13(EAN): 9783658083922 Издательство: Springer Рейтинг: Цена: 9141.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Matthias Kaeding discusses Bayesian methods for analyzing discrete and continuous failure times where the effect of time and/or covariates is modeled via P-splines and additional basic function expansions, allowing the replacement of linear effects by more general functions.
Описание: Detect fraud earlier to mitigate loss and prevent cascading damage Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques is an authoritative guidebook for setting up a comprehensive fraud detection analytics solution.
This volume of the Biostatistics and Health Sciences Set focuses on statistics applied to clinical research. The use of SAS for data management and statistical modeling is illustrated using various examples. Many aspects of data processing and statistical analysis of cross-sectional and experimental medical data are covered, including regression models commonly found in medical statistics.
This practical book is primarily intended for health researchers with a basic knowledge of statistical methodology. Assuming basic concepts, the authors focus on the practice of biostatistical methods essential to clinical research, epidemiology and analysis of biomedical data (including comparison of two groups, analysis of categorical data, ANOVA, linear and logistic regression, and survival analysis). The use of examples from clinical trials and epidemiological studies provide the basis for a series of practical exercises, which provide instruction and familiarize the reader with essential SAS commands.
Presents the use of SAS software in the statistical approach for the management of data modeling
Includes elements of the language and descriptive statistics
Supplies measures of association, comparison of means, and proportions for two or more samples
Explores linear and logistic regression
Provides survival data analysis
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