Data Mining and Analysis: Fundamental Concepts and Algorithms

Editorial Reviews

The fundamental in data mining and form the basis for the emerging field of data science, which includes automated methods to analyze patterns and models for all kinds of data, with applications ranging from discovery to and . This textbook for senior undergraduate and graduate data mining courses provides a broad yet in-depth overview of data mining, integrating related concepts from machine learning and statistics. The main parts of the book include exploratory data analysis, pattern mining, clustering, and classification. The book lays the basic foundations of these tasks, and also covers cutting-edge topics such as kernel methods, high-dimensional data analysis, and complex graphs and networks. With its comprehensive coverage, perspective, and wealth of examples, this book offers solid guidance in data mining for students, researchers, and practitioners alike.

Key features

  • Covers both core methods and cutting-edge research
  • Algorithmic approach with open-source implementations
  • Minimal prerequisites: all key concepts are presented, as is the intuition behind the formulas
  • Short, self-contained chapters with class-tested examples and exercises allow for flexibility in designing a course and for easy reference
  • Supplementary website with lecture slides, videos, ideas, and more

Table of Contents

Chapter 1 Data Mining and Analysis

Part I Data Analysis Foundations
Chapter 2 Numeric Attributes
Chapter 3 Categorical Attributes
Chapter 4 Data
Chapter 5 Kernel Methods
Chapter 6 High-Dimensional Data
Chapter 7 Dimensionality Reduction

Part II Frequent Pattern Mining
Chapter 8 Itemset Mining
Chapter 9 Summarizing Itemsets
Chapter 10 Sequence Mining
Chapter 11 Graph Pattern Mining
Chapter 12 Pattern and Rule Assessment

Part III Clustering
Chapter 13 Representative-based Clustering
Chapter 14 Hierarchical Clustering
Chapter 15 -based Clustering
Chapter 16 Spectral and Graph Clustering
Chapter 17 Clustering Validation

Part IV Classification
Chapter 18 Probabilistic Classification
Chapter 19 Decision Tree Classifier
Chapter 20 Linear Discriminant Analysis
Chapter 21 Support Vector Machines
Chapter 22 Classification Assessment

Book Details

QR code for Data Mining and Analysis: Fundamental Concepts and Algorithms
Read More Details on Google Books

Book Preview

Data Mining and Analysis: Fundamental Concepts and Algorithms is available read online. Click to Read Sample Chapters Online

Book Reviews

Read all Data Mining and Analysis: Fundamental Concepts and Algorithms Reviews on Amazon or Goodreads

PDF eBook Free Download

Data Mining and Analysis: Fundamental Concepts and Algorithms PDF FREE DOWNLOAD in 14 Friendly File Hosts: FireDrive, ZippyShare, SockShare, ShareBeast, BayFiles, Crocko, MixtureCloud, Depositfiles, UptoBox, Uploaded, BitShare, RapidGator, TurboBit. Report Dead Links & Get a Copy

Enjoyed this Book? Please support the author, Don't Download It, buy this book from amazon.

File HosteBook Free Download LinkFormatSize (MB)ThanksUpload Date
EU(multi)http://www.embedupload.com/?d=5AAALHR4MSDRAFT9.7foxebook10/08/2013

None of the files shown here are hosted or transmitted by this server. The links are provided solely by this site’s users. You may not use this site to distribute or download any material when you do not have the legal rights to do so. It is your own responsibility to adhere to these terms. Found illegal content? Let us know! REPORT ABUSE

Leave a Reply

Your email address will not be published. Required fields are marked *

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <strike> <strong>