Book Image

Rapid - Apache Mahout Clustering designs

Book Image

Rapid - Apache Mahout Clustering designs

Overview of this book

Related Content you might be interested in

Current Title:

Small book image
Rapid - Apache Mahout Clustering designs
Oct, 2015 | 130 pages
No titles found
Table of Contents (16 chapters)
Apache Mahout Clustering Designs
Apache Mahout Clustering Designs
Credits
Credits
About the Author
About the Author
About the Reviewers
About the Reviewers
www.PacktPub.com
www.PacktPub.com
Preface
Preface
Free Chapter
1
Understanding Clustering
Understanding Clustering
The clustering concept
Understanding distance measures
Understanding different clustering techniques
Algorithm support in Mahout
Clustering algorithms in Mahout
Installing Mahout
Preparing data for use with clustering techniques
Summary
2
Understanding K-means Clustering
Understanding K-means Clustering
Learning K-means
Visualizing clusters
Summary
3
Understanding Canopy Clustering
Understanding Canopy Clustering
Running Canopy clustering on Mahout
Visualizing clusters
Working with CSV files
Summary
4
Understanding the Fuzzy K-means Algorithm Using Mahout
Understanding the Fuzzy K-means Algorithm Using Mahout
Learning Fuzzy K-means clustering
Visualizing clusters
Summary
5
Understanding Model-based Clustering
Understanding Model-based Clustering
Learning model-based clustering
Running LDA using Mahout
Summary
6
Understanding Streaming K-means
Understanding Streaming K-means
Learning Streaming K-means
Using Mahout for streaming K-means
Summary
7
Spectral Clustering
Spectral Clustering
Understanding spectral clustering
Mahout implementation of spectral clustering
Summary
8
Improving Cluster Quality
Improving Cluster Quality
Evaluating clusters
Using DistanceMeasure interface
Summary
9
Creating a Cluster Model for Production
Creating a Cluster Model for Production
Preparing the dataset
Launching the Mahout job on the cluster
Performance tuning for the job
Summary
Index
Index

About the Author

Ashish Gupta has been working in the field of software development for the last 10 years. He has worked in companies such as SAP Labs and Caterpillar as a software developer. While working for a start-up predicting potential customers for new fashion apparels using social media, he developed an interest in the field of machine learning. Since then, he has worked on big data technologies and machine learning for different industries, including retail, finance, insurance, and so on. He is passionate about learning new technologies and sharing that knowledge with others. He is the author of the book, Learning Apache Mahout Classification, Packt Publishing. He has organized many boot camps for Apache Mahout and the Hadoop ecosystem.

First of all, I would like to thank the open source communities for their continuous efforts in developing great software. I would also like to thank the reviewers of this book.

Nothing can be accomplished without the support of family, friends, and loved ones; I would like to thank them, especially my wife and son, for their continuous support while writing this book.

Previous Section
Next Chapter