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Instant Weka How-to

Book Description

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

  • Learn something new in an Instant! A short, fast, focused guide delivering immediate results

  • A practical guide with examples and applications of programming Weka in Java

  • Start with the basics and dive deeper into the more advanced aspects of Weka

  • Learn how to include Weka’s machinery in your Java application

In Detail

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

  1. Instant Weka How-to
    1. Instant Weka How-to
    2. Credits
    3. About the Author
    4. About the Reviewer
    5. www.PacktPub.com
      1. Support files, eBooks, discount offers and more
        1. Why Subscribe?
        2. Free Access for Packt account holders
    6. Preface
      1. What this book covers
      2. What you need for this book
      3. Who this book is for
      4. Conventions
      5. Reader feedback
      6. Customer support
        1. Downloading the example code
        2. Errata
        3. Piracy
        4. Questions
    7. 1. Instant Weka How-to
      1. Starting with Java and Weka (Simple)
        1. Getting ready
        2. How to do it...
        3. How it works...
        4. There's more...
          1. Check if JDK is installed
          2. Working with Eclipse
      2. Loading the data (Simple)
        1. How to do it...
        2. How it works...
        3. There's more...
          1. Creating a dataset in runtime
          2. Saving the dataset to ARFF file
      3. Filtering attributes (Simple)
        1. How to do it...
        2. How it works...
        3. There's more...
          1. Attribute discretization
          2. Classifier-specific filter
      4. Selecting attributes (Intermediate)
        1. Getting ready
        2. How to do it...
        3. How it works...
        4. There's more...
          1. Select attributes using information gain
          2. Principal component analysis
          3. Classifier-specific selection
      5. Training a classifier (Simple)
        1. Getting ready
        2. How to do it...
        3. How it works...
        4. There's more...
          1. Support vector machine
          2. Other classification models
          3. Incremental classifiers
      6. Building your own classifier (Advanced)
        1. How to do it...
        2. How it works...
      7. Tree visualization (Intermediate)
        1. How to do it...
        2. How it works...
      8. Testing and evaluating your models (Simple)
        1. How to do it...
        2. How it works...
        3. There's more...
          1. Train and test set
          2. Other statistics
          3. Confusion matrix
          4. ROC curve
      9. Regression models (Simple)
        1. Getting ready
        2. How to do it...
        3. How it works...
        4. There's more...
          1. Other regression algorithms
      10. Association rules (Intermediate)
        1. Getting ready
        2. How to do it...
        3. How it works...
      11. Clustering (Simple)
        1. Getting ready
        2. How to do it...
        3. How it works...
        4. There's more...
          1. Cluster classification
          2. Incremental clustering
          3. Cluster evaluation
      12. Reusing models (Intermediate)
        1. How to do it...
        2. How it works...
      13. Data mining in direct marketing (Simple)
        1. Getting ready
        2. How to do it...
        3. How it works...
      14. Using Weka for stock value forecasting (Advanced)
        1. Getting ready
        2. How to do it...
        3. How it works...
      15. Recommendation system (Advanced)
        1. Getting ready
        2. How to do it...
        3. How it works...