airbnb-new-user-bookings

Predict which country a new user will make his or her first booking.
Link to the kaggle challenge: https://www.kaggle.com/c/airbnb-recruiting-new-user-bookings

Getting Started

Install anaconda or miniconda. Then create the environment with conda.

$ conda env create -f environment.yml

Download data

Download the Airbnb data here.

Create data and results directory

i.e.

$ mkdir data results

Generating train and test files

Run the following script to generate the processed train and test files.

$ python preprocess.py

Use the -d flag to change your data directory (default: 'data').

Training Models

To install lightgbm and xgboost, see the lightgbm install guide and xgboost install guide.

$ python train.py -h
usage: train.py [-h] [-d DATA_DIR] [-r RESULTS_DIR]
                [-m {all,logistic,tree,forest,ada,xgb}]
                [-s {random,smote,adasyn,smoteenn,none}] [-k K_FOLDS]
                [--device {cpu,gpu}]

Airbnb New User Booking Classification

optional arguments:
  -h, --help            show this help message and exit
  -d DATA_DIR           data directory
  -r RESULTS_DIR        results save directory
  -m {all,logistic,tree,forest,ada,xgb}
                        model
  -s {random,smote,adasyn,smoteenn,none}
                        sampling method
  -k K_FOLDS            number of CV folds
  --device {cpu,gpu}    device

To use lightgbm, run:

$ python lightgbm_train.py

Results

See cross validation output in the results directory in the form of pickle files.
To print a summary, run the following:

$ python summarize.py