Introduction to the Weka framework

One of the handy tools in evaluating various data science algorithms is Weka (Waikato Environment for Knowledge Analysis). This is a suite of machine learning software written in the Java programming language. Weka is very popular since it can be extended to leverage additional algorithms and data mining techniques. In this section, we will be introduced to the generic concepts of Weka and specifically look at using it for the implementation of genetic algorithms. 

Weka provides a great and intuitive visual user interface for data mining, analysis, and predictive modeling. Some of the features that make Weka a popular choice for the community are the following:

• Weka is available as a free tool to use under the GNU General Public license
• Weka is written in the Java programming language and compiles to byte code, which is easily portable across platforms
• Weka contains a rich library of machine learning algorithms and it can further be extended within the framework...