Statistics

Statistical Learning & Data Mining

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Industrial Applications of Machine Learning

1st Edition

Pedro Larrañaga, David Atienza, Javier Diaz-Rozo, Alberto Ogbechie, Carlos Esteban Puerto-Santana, Concha Bielza
August 15, 2018

"This book brings machine learning techniques to the IIoT community through a story that is able to be understood and applied by engineers and practitioners traditionally distanced from these techniques. Testbeds fuel the advancement of the IIoT with results from real-world data that can be applied...

Compositional Data Analysis in Practice

1st Edition

Michael Greenacre
August 01, 2018

Compositional Data Analysis in Practice is a user-oriented practical guide to the analysis of data with the property of a constant sum, for example percentages adding up to 100%. Compositional data can give misleading results if regular statistical methods are applied, and are best analysed by...

Sparse Optimization Theory and Methods

1st Edition

Yun-Bin Zhao
July 09, 2018

Seeking sparse solutions of underdetermined linear systems is required in many areas of engineering and science such as signal and image processing. The efficient sparse representation becomes central in various big or high-dimensional data processing, yielding fruitful theoretical and realistic...

Sufficient Dimension Reduction: Methods and Applications with R

1st Edition

Bing Li
May 01, 2018

Sufficient dimension reduction is a rapidly developing research field that has wide applications in regression diagnostics, data visualization, machine learning, genomics, image processing, pattern recognition, and medicine, because they are fields that produce large datasets with a large number of...

Spectral Feature Selection for Data Mining

1st Edition

Zheng Alan Zhao, Huan Liu
April 18, 2018

Spectral Feature Selection for Data Mining introduces a novel feature selection technique that establishes a general platform for studying existing feature selection algorithms and developing new algorithms for emerging problems in real-world applications. This technique represents a unified...

Exploratory Data Analysis Using R

1st Edition

Ronald K. Pearson
April 06, 2018

Exploratory Data Analysis Using R provides a classroom-tested introduction to exploratory data analysis (EDA) and introduces the range of "interesting" – good, bad, and ugly – features that can be found in data, and why it is important to find them. It also introduces the mechanics of using R to...

Feature Engineering for Machine Learning and Data Analytics

1st Edition

Guozhu Dong, Huan Liu
April 04, 2018

Feature engineering plays a vital role in big data analytics. Machine learning and data mining algorithms cannot work without data. Little can be achieved if there are few features to represent the underlying data objects, and the quality of results of those algorithms largely depends on the...

Data Stewardship for Open Science: Implementing FAIR Principles

1st Edition

Barend Mons
March 05, 2018

Data Stewardship for Open Science: Implementing FAIR Principles has been written with the intention of making scientists, funders, and innovators in all disciplines and stages of their professional activities broadly aware of the need, complexity, and challenges associated with open science, modern...

High Performance Computing for Big Data: Methodologies and Applications

1st Edition

Chao Wang
October 10, 2017

High-Performance Computing for Big Data: Methodologies and Applications explores emerging high-performance architectures for data-intensive applications, novel efficient analytical strategies to boost data processing, and cutting-edge applications in diverse fields, such as machine learning, life...

Frontiers in Data Science

1st Edition

Matthias Dehmer, Frank Emmert-Streib
October 09, 2017

Frontiers in Data Science deals with philosophical and practical results in Data Science. A broad definition of Data Science describes the process of analyzing data to transform data into insights. This also involves asking philosophical, legal and social questions in the context of data generation...

Big Data Analytics in Cybersecurity

1st Edition

Onur Savas, Julia Deng
September 20, 2017

Big data is presenting challenges to cybersecurity. For an example, the Internet of Things (IoT) will reportedly soon generate a staggering 400 zettabytes (ZB) of data a year. Self-driving cars are predicted to churn out 4000 GB of data per hour of driving. Big data analytics, as an emerging...

Introduction to Machine Learning with Applications in Information Security

1st Edition

Mark Stamp
September 07, 2017

Introduction to Machine Learning with Applications in Information Security provides a class-tested introduction to a wide variety of machine learning algorithms, reinforced through realistic applications. The book is accessible and doesn’t prove theorems, or otherwise dwell on mathematical theory....

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