4. Download and install the WEKA data mining toolkit. It is available through this link: http://www.cs.waikato.ac.nz/ml/weka/downloading.html

Then use the Explorer GUI interface and open the "credit-g.arff" data set that is included in WEKA (data directory). This is a data set from Germany describing credit-worthiness (good or bad) of customers based on 20 different attributes. Go to the classify tab, select "Percentage Split" and enter 50%. Then run each of the following classification algorithms:

trees.J48

trees.SimpleCart

trees.RandomForests

meta.AdaBoostM1

a) For each algorithm, report the accuracy, precision, and recall values with default parameters

b) Adjust the parameters of each algorithm to maximize the accuracy. Report the algorithm and parameter settings that maximized the accuracy measure and provide the maximum accuracy value.