Master the art of predictive modelingAbout This BookLoad, wrangle, and analyze your data using the world's most powerful statistical programming languageFamiliarize yourself with the most common data mining tools of R, such as k-means, hierarchical regression, linear regression, Naive Bayes, decision trees, text mining and so on.We emphasize important concepts, such as the bias-variance trade-off and over-fitting, which are perva...

Get to grips with key data visualization and predictive analytic skills using R Key FeaturesAcquire predictive analytic skills using various tools of RMake predictions about future events by discovering valuable information from data using RComprehensible guidelines that focus on predictive model design with real-world dataBook DescriptionThis book is packed with easy-to-follow guidelines that explain the workings of the many...

Gender and Social Hierarchies offers a fresh and coherent picture of applied research from within social psychology on the intricate relationship between gender and social status. It comprises a collection of innovative approaches which seek to understand the pervasiveness of status asymmetry between gender categories. Drawing upon recent theoretical advances in gender psychology, the book provides tools for developing practical and political recommendations to address and resolve...

Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the...

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analyticsKey FeaturesLeverage Python’s most powerful open-source libraries for deep learning, data wrangling, and data visualizationLearn effective strategies and best practices to improve and optimize machine learning systems and algorithmsAsk – and answer – tough questions of your data with robust statistical models, built for a range of datasets...

Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain...

Explains the various techniques of PPM development, simulation and optimization. All the explanations are given with IT industry and usage of alternate techniques to build PPM to suit even smaller organizations. Application of Statistical, Probablistic and Simulation models are elaborated.

Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge. Data mining is usually associated with a business or an organization's need to identify trends and profiles, allowing, for example, retailers to discover patterns on which to base marketing objectives.This book looks at both classical and ...

Using R for Statistics will get you the answers to most of the problems you are likely to encounter when using a variety of statistics. This book is a problem-solution primer for using R to set up your data, pose your problems and get answers using a wide array of statistical tests. The book walks you through R basics and how to use R to accomplish a wide variety statistical operations.You'll be able to navigate the R system, enter and import data, manipulate datasets, ca...

This book presents the basic procedures for utilizing SAS Enterprise Guide to analyze statistical data. SAS Enterprise Guide is a graphical user interface (point and click) to the main SAS application. Each chapter contains a brief conceptual overview and then guides the reader through concrete step-by-step examples to complete the analyses. The eleven sections of the book cover a wide range of statistical procedures including descriptive statistics, correlation and simple regression, t te...

Load, wrangle, and analyze your data using the world\\'s most powerful statistical programming languageKey Features\[\*\]Load, manipulate and analyze data from different sources\[\*\]Gain a deeper understanding of fundamentals of applied statistics\[\*\]A practical guide to performing data analysis in practiceBook DescriptionFrequently the tool of choice for academics, R has spread deep into the private sector and can be foun...

Build Machine Learning models with a sound statistical understanding.Key FeaturesLearn about the statistics behind powerful predictive models with p-value, ANOVA, and F- statistics.Implement statistical computations programmatically for supervised and unsupervised learning through K-means clustering.Master the statistical aspect of Machine Learning with the help of this example-rich guide to R and Python.Book DescriptionCompl...