Instant Weka How-to [Instant]
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- 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
Book DetailsLanguage : English
eBook : 80 pages
Release Date : June 2013
ISBN : 1782163867
ISBN 13 : 9781782163862
Author(s) : Boštjan Kaluža
Topics and Technologies : All Books, Big Data and Business Intelligence, Instant, Java, Open Source
Table of ContentsPreface
Instant Weka How-to
- 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)
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What you will learn from this book
- 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
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.
Filled with practical, step-by-step instructions and clear explanations for the most important and useful tasks. A practical guide with examples and applications of programming Weka in Java.
Who this book is for
This book primarily targets Java developers who want to build Weka’s data mining capabilities into their projects. Computer science students, data scientists, artificial intelligence programmers, and statistical programmers would equally gain from this book and would learn about essential tasks required to implement a project. Experience with Weka concepts is assumed.