9781787284395
Machine Learning with R Cookbook Second Edition 版次: Analyze data and build predictive models
by: AshishSingh Bhatia – Yu-Wei,Chiu (David Chiu)
ISBN-10: 1787284395
ISBN-13: 9781787284395
Edition 版次: 2nd Revised edition
Publication Date 出版日期: 2017-12-11
Print Length 页数: 572
Book Description
By finelybook
Big data has become a popular buzzword across many industries. An increasing number of people have been exposed to the term and are looking at how to leverage big data in their own businesses,to improve sales and profitability. However,collecting,aggregating,and visualizing data is just one part of the equation. Being able to extract useful information from data is another task,and a much more challenging one. Machine Learning with R Cookbook,Second Edition uses a practical approach to teach you how to perform machine learning with R. Each chapter is divided into several simple recipes. Through the step-by-step instructions provided in each recipe,you will be able to construct a predictive model by using a variety of machine learning packages. In this book,you will first learn to set up the R environment and use simple R commands to explore data. The next topic covers how to perform statistical analysis with machine learning analysis and assess created models,covered in detail later on in the book. You’ll also learn how to integrate R and Hadoop to create a big data analysis platform. The detailed illustrations provide all the information required to start applying machine learning to individual projects. With Machine Learning with R Cookbook,machine learning has never been easier.
Contents
1: PRACTICAL MACHINE LEARNING WITH R
2: DATA EXPLORATION WITH AIR QUALITY DATASETS
3: ANALYZING TIME SERIES DATA
4: R AND STATISTICS
5: UNDERSTANDING REGRESSION ANALYSIS
6: SURVIVAL ANALYSIS
7: CLASSIFICATION 1 – TREE,LAZY,AND PROBABILISTIC
8: CLASSIFICATION 2 – NEURAL NETWORK AND SVM
9: MODEL EVALUATION
10: ENSEMBLE LEARNING
11: CLUSTERING
12: ASSOCIATION ANALYSIS AND SEQUENCE MINING
13: DIMENSION REDUCTION
14: BIG DATA ANALYSIS (R AND HADOOP)
What You Will Learn
Create and inspect transaction datasets and perform association analysis with the Apriori algorithm
Visualize patterns and associations using a range of graphs and find frequent item-sets using the Eclat algorithm
Compare differences between each regression method to discover how they solve problems
Detect and impute missing values in air quality data
Predict possible churn users with the classification approach
Plot the autocorrelation function with time series analysis
Use the Cox proportional hazards model for survival analysis
Implement the clustering method to segment customer data
Compress images with the dimension reduction method
Incorporate R and Hadoop to solve machine learning problems on big data
Authors
Ashishsingh Bhatia
AshishSingh Bhatia is a reader and learner at his core. He has more than 11 years of rich experience in different IT sectors,encompassing training,development,and management. He has worked in many domains,such as software development,ERP,banking,and training. He is passionate about Python and Java,and recently he has been exploring R. He is mostly involved in web and mobile developments in various capacity. He always likes to explore new technologies and share his views and thoughts through various online medium and magazines. He believes in sharing his experience with new generation and do take active part in training and teaching also.
Yu-Wei,Chiu (David Chiu)
Yu-Wei,Chiu (David Chiu) is the founder of LargitData Company. He has previously worked for Trend Micro as a software engineer,with the responsibility of building up big data platforms for business intelligence and customer relationship management systems. In addition to being a startup entrepreneur and data scientist,he specializes in using Spark and Hadoop to process big data and apply data mining techniques to data analysis. Yu-Wei is also a professional lecturer,and has delivered talks on Python,R,Hadoop,and tech talks at a variety of conferences.
In 2013,Yu-Wei reviewed Bioinformatics with R Cookbook,a book compiled for Packt Publishing.
