This repo contains my code for entry in my first Kaggle competition - What's Cooking. The code generated a best submission of 133/1388 entries, which is within the top 10% of entries (though this needs to be verified as final results are still being validated).
The code was heavily inspired by an entry for a past Kaggle competition entry by @emanuele: https://github.com/emanuele/kaggle_pbr/blob/master/blend.py. The code builds a stacking model consisting of a:
- Logistic Regression classifier
- Bernoulli Naive Bayes
- Linear Support Vector Machine
- Random Forest Classifier
- Extra Trees Ensemble Classifier
- and Bagging Classifier using averaged Logistic Regression classifiers.
A final Logistic Regression classifier was trained on the class probabilities predicted from each of these component models, and this model was used to make predictions for the final submission.