Hartigan, J. A., and M. A. Wong. "Algorithm AS 136: A K-Means Clustering Algorithm". Journal of the Royal Statistical Society, Series C 28 (1): 100–108. JSTOR 2346830. 1979.
Sundberg, Rolf. Maximum likelihood theory and applications for distributions generated when observing a function of an exponential family variable. Dissertation. Institute for Mathematical Statistics. Stockholm University. 1971.
Bacao, Fernando, Victor Lobo, and Marco Painho. Self-organizing Maps as Substitutes for K-Means Clustering. CS 2005, LNCS 3516, 476–483. 2005.
Jolliffe, I.T. Principal Component Analysis, Series: Springer Series in Statistics. 2nd ed., Springer, NY, 2002. 2002.
Clojure for Machine Learning
By :
Clojure for Machine Learning
By:
Overview of this book
<p>Clojure for Machine Learning is an introduction to machine learning techniques and algorithms. This book demonstrates how you can apply these techniques to real-world problems using the Clojure programming language.</p>
<p>It explores many machine learning techniques and also describes how to use Clojure to build machine learning systems. This book starts off by introducing the simple machine learning problems of regression and classification. It also describes how you can implement these machine learning techniques in Clojure. The book also demonstrates several Clojure libraries, which can be useful in solving machine learning problems.</p>
<p>Clojure for Machine Learning familiarizes you with several pragmatic machine learning techniques. By the end of this book, you will be fully aware of the Clojure libraries that can be used to solve a given machine learning problem.</p>
Table of Contents (17 chapters)
Clojure for Machine Learning
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Free Chapter
Working with Matrices
Understanding Linear Regression
Categorizing Data
Building Neural Networks
Selecting and Evaluating Data
Building Support Vector Machines
Clustering Data
Anomaly Detection and Recommendation
Large-scale Machine Learning
References
Index
Customer Reviews