Airbnb_predictive_analysis

For Developers and Researchers

Please go check the file ./Library/utils.R to see a set of utility functions that I (Chacoon3) wrote to speed up the machine learning workflow.

Introduction

• This is the winner machine learning project of my master program's machine learning contest. It contains visualizations, datasets, documents, team-developed R libraries, trained models, as well as source codes.

• In this project, the repository owner along with other four teammates collaborated to train machine learning models that best ranks the popularity of Airbnb accomodations as were measured by a categorical target variable high_booking_rate.

• The most important codes of this project are in three files, namely main.r, utils.r, and data_cleaning.r. The latter two files are under the folder "Library".

• We finalized with a XGBoost model which had its AUC being 0.903, the highest AUC among all the teams that parcipated in this competition.