Weka is a suite of machine learning software for data mining tasks. Weka is used at universities throughout the world to teach data mining processes. It is very similar to much more expensive software and does a great job. Weka is the product of the University of Waikato in New Zealand and was first implemented in its modern form in 1997. It uses the GNU General Public License (GPL). The software is written in the Java™ language and contains a GUI for interacting with data files and producing visual results.
View the following video for an introduction to Weka:
Once you finish viewing all the video tutorials and have successfully installed Weka, please open the data file “diabetes.arff” and classify the data using the decision tree algorithm (J48). Your report will include a combination of screenshots and written work. In your report, please include:
A screenshot of Weka Explore when the file “diabetes.arff” is successfully loaded
A screenshot of Weka Explore when the classification is completed
After viewing the classification results, please explain the confusion matrix, e.g., what are the True Positive (TP) number, the True Negative (TN) number, the False Positive (FP) number, and the False Negative (FN) number?
Please use “Visualize tree” to view the decision tree and include a screenshot of the tree in your report. (100 words)