in this exercise you will train different classifiers on a training data$-$set and for each

classifier you will report its accuracy and the confusion matrix. Based on the classifier

accuracy you will choose the best classifier $($best model learned from the training data$)$

and will use the model to predict the class labels for each sample in the test data.

Download the $$zoo$.$arff$$ data$-$set from the class website. Use this data set to train the

following Weka classifiers. $($you need to tweak the parameter$($s$)$ specified for each

classifier and choose the value for that parameter which would cause the classifier having

the lowest error rate$)$