##Folders
-
"cooking_code" folder : All of the code (and the input) goes here. We use scikit-learn's implementation of our learning algorithms.
- cooking_util contains reusable code and is meant to be imported as a module. It includes:
- a function that loads the data
- a function that cleans the data using Elad's cleaning method
- a class that makes the data into numpy arrays
- a function that creates a submission file, using a prediction function
- log_reg.py uses scikit-learn's logistic regression with Elad's cleaning method
- random_forest.py uses scikit-learn's random forest with Elad's cleaning method
- log_reg_bag_of_words.py uses scikit-learn's logistic regression with the bag of words cleaning method
- random_forest_bag_of_words.py uses scikit-learn's random_forest with the bag of words cleaning method
- cooking_util contains reusable code and is meant to be imported as a module. It includes:
-
"cooking_output” folder : Submission files generated by the algorithms
- kaggle_scores.txt stores the csv files' accuracies on submission to Kaggle.