
proportionsTest that will always give the same results
bayes: 0.909+-0.009 tree: 0.875+-0.033 default: 0.611+-0.000
bayes: 0.909+-0.009 tree: 0.875+-0.033 default: 0.611+-0.000
bayes: 0.909+-0.009 tree: 0.875+-0.033 default: 0.611+-0.000

proportionsTest that will give different results, but the same each time the script is run
bayes: 0.909+-0.009 tree: 0.875+-0.033 default: 0.611+-0.000
bayes: 0.912+-0.014 tree: 0.852+-0.039 default: 0.611+-0.000
bayes: 0.903+-0.019 tree: 0.857+-0.029 default: 0.611+-0.000

proportionsTest + storing classifiers
#iter 100, #classifiers 3

Good old 10-fold cross validation
bayes: 0.903+-0.016 tree: 0.825+-0.030 default: 0.614+-0.005

Learning curve
0.200: bayes: 0.899+-0.037 tree: 0.897+-0.052 default: 0.614+-0.006
0.400: bayes: 0.922+-0.022 tree: 0.929+-0.042 default: 0.614+-0.006
0.600: bayes: 0.899+-0.008 tree: 0.897+-0.057 default: 0.614+-0.006
0.800: bayes: 0.903+-0.017 tree: 0.883+-0.031 default: 0.614+-0.006
1.000: bayes: 0.901+-0.017 tree: 0.811+-0.025 default: 0.614+-0.006

Learning curve with pre-separated data
0.200: bayes: 0.922+-0.014 tree: 0.918+-0.016 default: 0.611+-0.000
0.400: bayes: 0.934+-0.004 tree: 0.937+-0.014 default: 0.611+-0.000
0.600: bayes: 0.925+-0.012 tree: 0.904+-0.015 default: 0.611+-0.000
0.800: bayes: 0.911+-0.014 tree: 0.902+-0.007 default: 0.611+-0.000
1.000: bayes: 0.908+-0.000 tree: 0.893+-0.000 default: 0.611+-0.000

Learning and testing on pre-separated data
bayes: 0.908+-0.014 tree: 0.901+-0.015 default: 0.611+-0.041

Learning and testing on the same data
bayes: 0.903+-0.008 tree: 0.998+-0.000 default: 0.614+-0.022
