
proportionsTest that will always give the same results
bayes: 0.909+-0.009    tree: 0.954+-0.006    default: 0.611+-0.000   
bayes: 0.909+-0.009    tree: 0.954+-0.006    default: 0.611+-0.000   
bayes: 0.909+-0.009    tree: 0.954+-0.006    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: 0.954+-0.006    default: 0.611+-0.000   
bayes: 0.912+-0.014    tree: 0.950+-0.010    default: 0.611+-0.000   
bayes: 0.903+-0.019    tree: 0.953+-0.012    default: 0.611+-0.000   

proportionsTest + storing classifiers
#iter 100, #classifiers 3


Good old 10-fold cross validation
bayes: 0.903+-0.016    tree: 0.954+-0.024    default: 0.614+-0.005   

Learning curve
0.200: bayes: 0.899+-0.037    tree: 0.938+-0.035    default: 0.614+-0.006   
0.400: bayes: 0.922+-0.022    tree: 0.938+-0.021    default: 0.614+-0.006   
0.600: bayes: 0.899+-0.008    tree: 0.943+-0.027    default: 0.614+-0.006   
0.800: bayes: 0.903+-0.017    tree: 0.940+-0.028    default: 0.614+-0.006   
1.000: bayes: 0.901+-0.017    tree: 0.938+-0.025    default: 0.614+-0.006   

Learning curve with pre-separated data
0.200: bayes: 0.922+-0.014    tree: 0.927+-0.029    default: 0.611+-0.000   
0.400: bayes: 0.934+-0.004    tree: 0.950+-0.012    default: 0.611+-0.000   
0.600: bayes: 0.925+-0.012    tree: 0.939+-0.013    default: 0.611+-0.000   
0.800: bayes: 0.911+-0.014    tree: 0.948+-0.011    default: 0.611+-0.000   
1.000: bayes: 0.908+-0.000    tree: 0.969+-0.000    default: 0.611+-0.000   

Learning and testing on pre-separated data
bayes: 0.908+-0.014    tree: 0.969+-0.005    default: 0.611+-0.041   

Learning and testing on the same data
bayes: 0.903+-0.008    tree: 0.977+-0.002    default: 0.614+-0.022   
