Applied Unsupervised Learning with R: Uncover hidden relationships and patterns with k-means clustering,hierarchical clustering,and PCA
Authors: Alok Malik – Bradford Tuckfield
ISBN-10: 1789956390
ISBN-13: 9781789956399
Publication Date 出版日期: 2019-03-27
Print Length 页数: 320 pages
Book Description
By finelybook
Starting with the basics,Applied Unsupervised Learning with R explains clustering methods,distribution analysis,data encoders,and features of R that enable you to understand your data better and get answers to your most pressing business questions.
This book begins with the most important and commonly used method for unsupervised learning – clustering – and explains the three main clustering algorithms – k-means,divisive,and agglomerative. Following this,you’ll study market basket analysis,kernel density estimation,principal component analysis,and anomaly detection. You’ll be introduced to these methods using code written in R,with further instructions on how to work with,edit,and improve R code. To help you gain a practical understanding,the book also features useful tips on applying these methods to real business problems,including market segmentation and fraud detection. By working through interesting activities,you’ll explore data encoders and latent variable models.
By the end of this book,you will have a better understanding of different anomaly detection methods,such as outlier detection,Mahalanobis distances,and contextual and collective anomaly detection.
Contents
1: INTRODUCTION TO CLUSTERING METHODS
2: ADVANCED CLUSTERING METHODS
3: PROBABILITY DISTRIBUTIONS
4: DIMENSION REDUCTION
5: DATA COMPARISON METHODS
6: ANOMALY DETECTION
What You Will Learn
Implement clustering methods such as k-means,agglomerative,and divisive
Write code in R to analyze market segmentation and consumer behavior
Estimate distribution and probabilities of different outcomes
Implement dimension reduction using principal component analysis
Apply anomaly detection methods to identify fraud
Design algorithms with R and learn how to edit or improve code
Authors
Alok Malik
Alok Malik is a data scientist based in India. He has previously worked on creating and deploying unsupervised learning solutions in fields such as finance,cryptocurrency trading,logistics,and natural language processing. He has a bachelor’s degree in technology from the Indian Institute of Information Technology,Design and Manufacturing,Jabalpur,where he studied electronics and communication engineering.
Bradford Tuckfield
Bradford Tuckfield has designed and implemented data science solutions for firms in a variety of industries. He studied math for his bachelor’s degree and economics for his Ph.D. He has written for scholarly journals and the popular press,on topics including linear algebra,psychology,and public policy.
