Instant Weka How-to

Implement cutting-edge data mining aspects in Weka to your applications

Instant Weka How-to

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Boštjan Kaluža

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Implement cutting-edge data mining aspects in Weka to your applications
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Book Details

ISBN 139781782163862
Paperback80 pages

Book Description

Data mining has become one of the hottest topics in computer science, mainly due to the vast amounts of data in diverse applications such as market basket analysis, reactive business intelligence, human genome sequence mining, speech recognition, document search, and spam detection.

Instant Weka How-to shows you exactly how to include Weka’s machinery in your Java application to stay ahead by implementing cutting-edge data-mining aspects such as regression and classification, and then moving on to more advanced applications of forecasting, decision making, and recommendations.

This book shows you exactly how to include Weka’s machinery in your Java application. The book starts by importing and preparing the data, and then moves on to more serious topics on classification, regression, clustering, and evaluation. For those of you who are eager to dive deeper, this book shows you how to implement online learning or how to create your own classifier. The book includes several application examples such as house price prediction, stock value forecasting, and decision making for direct marketing.

Table of Contents

Chapter 1: Instant Weka How-to
Starting with Java and Weka (Simple)
Loading the data (Simple)
Filtering attributes (Simple)
Selecting attributes (Intermediate)
Training a classifier (Simple)
Building your own classifier (Advanced)
Tree visualization (Intermediate)
Testing and evaluating your models (Simple)
Regression models (Simple)
Association rules (Intermediate)
Clustering (Simple)
Reusing models (Intermediate)
Data mining in direct marketing (Simple)
Using Weka for stock value forecasting (Advanced)
Recommendation system (Advanced)

What You Will Learn

  • Start to code with Weka and Java
  • Load the data
  • Select and filter attributes
  • Train a classifier
  • Create your own classifier
  • Test and evaluate your models
  • Construct regression models
  • Build association rules and clusters
  • Predict house value
  • Implement direct marketing applications

Authors

Table of Contents

Chapter 1: Instant Weka How-to
Starting with Java and Weka (Simple)
Loading the data (Simple)
Filtering attributes (Simple)
Selecting attributes (Intermediate)
Training a classifier (Simple)
Building your own classifier (Advanced)
Tree visualization (Intermediate)
Testing and evaluating your models (Simple)
Regression models (Simple)
Association rules (Intermediate)
Clustering (Simple)
Reusing models (Intermediate)
Data mining in direct marketing (Simple)
Using Weka for stock value forecasting (Advanced)
Recommendation system (Advanced)

Book Details

ISBN 139781782163862
Paperback80 pages
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