Expedia kaggle competition

Requirements

The development is made in python 3.5 or above and requires the following packages:

• numpy 1.12.1 or above
• pandas 19.2 or above
• xgboost 0.6 or above

Solution file generation

1. Clone the directory : git clone https://github.com/goldentom42/kaggle_expedia_2016.git
2. Download train and test data files from the Expedia competition page to the input folder.
3. Under the main directory run: python bayesian_approach.py --mode=sub --name=full This will generate a file in the submission folder.

If you want to play with the files

bayesian_approach.py supports several options:

• -b : this option will split the train.csv file into training and validation sets
• --mode=val : this option trains on the training set and issue statistics after building recommendations on the validation set.
• --mode=sub : this option trains on the original train.csv file and build recommendations for the test.csv file. It will generate a submission file in the submission folder. You can submit it on kaggle to check you LB position
• --keys=[comma separated list of fields] : with this option you can test different settings and see how the recommendations behave
• --name=[name of submission file] : with thos you can specify the name of the generated file
• -w[weighting startegy number] : supports 0, 1 and 2. Sets the weight assigned to each training samples

Examples:

• python bayesian_approach.py --mode=val --keys=user_location_city,orig_destination_distance --name=leak
• bayesian_approach.py --mode=sub --keys=srch_destination_id,hotel_market,is_package --name=dest_mkt_pack -w1