Group project on Machine Learning using WEKA (Walkato Environment for Knowledge Analysis)
Group members: Joshua Cohenour, Alexandria Carmichael, and Miguel Castro
WEKA is a suite of Machine Learning software written in Java. Algorithms can be applied in to a dataset or using an original Java code. To learn more about WEKA, visit: http://www.cs.waikato.ac.nz/ml/weka/
Josh wrote an algorithm for a weather application. In this case, the accuracy classifying for a windy day (True or False) and daily outlook (Sunny, Cloudy, or Rainy).
First and foremost, the Java code was run in a Java IDE (i.e. Eclipse), with the weka.jar imported in another seperate library.
The class is named "Project5MachineLearning", which takes a text file named "weather.txt", and reads the contents of said text file. Note: make sure that the text file is located in the same directory as the .java file.
The contents of weather.txt are data from April 2015-2017 weather report. Link here: https://www.wunderground.com/history/airport/KFAY/2015/4/21/MonthlyCalendar.html?req_city=Fayetteville&req_state=NC&req_statename=&reqdb.zip=28306&reqdb.magic=15&reqdb.wmo=99999&MR=1
The output of the Java code, "Project5MachineLearning", can be viewed in the text file named "results.txt."