For J48, set the "unpruned" option to True. You can use the default settings for all other parameters of J48, NaiveBayesSimple, and Logistic Regression. Optional: Rerun the experiments with pruning turned on and see if it makes any difference.
In addition to running Bagging and AdaBoostM1, you should rerun a single decision tree, a single Naive Bayes, and a single logistic regression.
hw2-1, hw2-2,
and br.
However, we will not construct learning curves this time. Instead, you
should just train
on the following three files:
Domain Training Data File Test Data File
BR br-train.arff br-test.arff
hw2-1 hw2-1-200.arff hw2-1-test.arff
hw2-2 hw2-2-200.arff hw2-2-test.arff
hw2-1:Where
Base learner Single Bagging Boosting
J48 xxx yyy zzz
Logistic xxx yyy zzz
NaiveBayes xxx yyy zzz
hw2-2:
Base learner Single Bagging Boosting
J48 xxx yyy zzz
Logistic xxx yyy zzz
NaiveBayes xxx yyy zzz
br:
Base learner Single Bagging Boosting
J48 xxx yyy zzz
Logistic xxx yyy zzz
NaiveBayes xxx yyy zzz
xxx gives the error rate of a single classifier of
the indicated Base
Learning, yyy gives the error rate of a bagging (30
iterations), and zzz gives the error rate of AdaboostM1
(maximum 30
iterations).