Learn IT - Books tags regression

Data Mining Using SAS Applications (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)

Springer, 2002

Most books on data mining focus on principles and furnish few instructions on how to carry out a data mining project. Data Mining Using SAS Applications not only introduces the key concepts but also enables readers to understand and successfully apply data mining methods using powerful yet user-friendly SAS macro-call files. These methods...

Linear Models with R (Chapman & Hall/CRC Texts in Statistical Science)

CRC Press, 2004

Books on regression and the analysis of variance abound-many are introductory, many are theoretical. While most of them do serve a purpose, the fact remains that data analysis cannot be properly learned without actually doing it, and this means using a statistical software package. There are many of these to choose from as well, all with...

Building Machine Learning Systems with Python

Packt Publishing, 2013

As the Big Data explosion continues at an almost incomprehensible rate, being able to understand and process it becomes even more challenging. With Building Machine Learning Systems with Python, you'll learn everything you need to tackle the modern data deluge - by harnessing the unique capabilities of Python and its extensive range of...

Introduction to Data Mining and its Applications (Studies in Computational Intelligence)

Springer, 2006

An enormous proliferation of databases in almost every area of human endeavor has created a great demand for new, powerful tools for turning data into useful, task-oriented knowledge. In the efforts to satisfy this need, researchers have been exploring ideas and methods developed in machine learning, pattern recognition, statistical data analysis,...

Mastering SQL Server 2014 Data Mining

Packt Publishing, 2014

Master selecting, applying, and deploying data mining models to build powerful predictive analysis frameworks

About This Book

Understand the different phases of data mining, along with the tools used at each stage

Explore the different data mining algorithms in depth

Become...

Genetic Programming Theory and Practice X (Genetic and Evolutionary Computation)

Springer, 2013

These contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP.

Topics in this volume include: evolutionary constraints,...

Artificial Intelligence and Machine Learning Fundamentals: Develop real-world applications powered by the latest AI advances

Packt Publishing, 2018

Create AI applications in Python and lay the foundations for your career in data science

Key Features

Practical examples that explain key machine learning algorithms

Explore neural networks in detail with interesting examples

Master core AI concepts with...

SAS/STAT 9.1 User's Guide, Volumes 1-7

Sams Publishing, 2004

SAS/STAT software provides extensive statistical capabilities with tools for both specialized and enterprise-wide analytical needs. It can help you analyze data and make informed decisions for research, engineering, manufacturing, medical, and business applications. This user's guide provides the latest, detailed reference material for the...

Statistics for Environmental Engineers, Second Edition

CRC Press, 2002

The book is well written, easy to read, and interesting, which is no small feat considering the subject matter. The authors have taken considerable steps to make this textbook user-friendly to their intended audience, environmental engineers. … The authors, both recognized experts in civil and sanitary engineering, provide data and problems...

Kernel Smoothing: Principles, Methods and Applications

John Wiley & Sons, 2018

Comprehensive theoretical overview of kernel smoothing methods with motivating examples

Kernel smoothing is a flexible nonparametric curve estimation method that is applicable when parametric descriptions of the data are not sufficiently adequate. This book explores theory and methods of kernel smoothing in a variety of...

Statistical Tools for Nonlinear Regression: A Practical Guide With S-PLUS and R Examples (Springer Series in Statistics)

Springer, 2003

Statistical Tools for Nonlinear Regression presents methods for analyzing data. It has been expanded to include binomial, multinomial and Poisson non-linear models. The examples are analyzed with the free software nls2 updated to deal with the new models included in the second edition. The nls2 package is implemented in S-PLUS and R....

Beginning R: The Statistical Programming Language

Wrox Press, 2012

This book is about data analysis and the programming language called R. This is rapidly becoming the de facto standard among professionals, and is used in every conceivable discipline from science and medicine to business and engineering.

R is more than just a computer program; it is a statistical programming environment and...

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