Kaggle-Ensemble-Guide

A combination of Model Ensembling methods that is extremely useful for increasing accuracy of Kaggle's submission. For more information: http://mlwave.com/kaggle-ensembling-guide/

Example:

$ python kaggle_vote.py "./samples/method*.csv" "./samples/kaggle_vote.csv"
parsing: ./samples/method1.csv
parsing: ./samples/method2.csv
parsing: ./samples/method3.csv
wrote to ./samples/kaggle_vote.csv

$ python kaggle_rankavg.py "./samples/method*.csv" "./samples/kaggle_rankavg.csv"
parsing: ./samples/method1.csv
parsing: ./samples/method2.csv
parsing: ./samples/method3.csv
wrote to ./samples/kaggle_rankavg.csv

$ python kaggle_avg.py "./samples/method*.csv" "./samples/kaggle_avg.csv"
parsing: ./samples/method1.csv
parsing: ./samples/method2.csv
parsing: ./samples/method3.csv
wrote to ./samples/kaggle_avg.csv

Result:

==> ./samples/method1.csv <==
ImageId,Label
1,1
2,0
3,9
4,9
5,3

==> ./samples/method2.csv <==
ImageId,Label
1,2
2,0
3,6
4,2
5,3

==> ./samples/method3.csv <==
ImageId,Label
1,2
2,0
3,9
4,2
5,3

==> ./samples/kaggle_avg.csv <==
ImageId,Label
1,1.666667
2,0.000000
3,8.000000
4,4.333333
5,3.000000

==> ./samples/kaggle_rankavg.csv <==
ImageId,Label
1,0.25
2,0.0
3,1.0
4,0.5
5,0.75

==> ./samples/kaggle_vote.csv <==
ImageId,Label
1,2
2,0
3,9
4,2
5,3