Recruit Ponpare is Japan’s leading joint coupon site, offering huge discounts on everything from hot yoga, to gourmet sushi, to a summer concert bonanza. The Recruit Coupon Purchase Prediction challenge asked the community to predict which coupons a customer would buy in a given period of time using past purchase and browsing behavior.
Halla Yang finished 2nd ahead of 1,191 other data scientists. His experience working with time series data helped him use unsupervised methods effectively in conjunction with gradient boosting. In this blog, Halla walks through his approach and shares key visualizations that helped him better understand and work with the dataset.
The Basics
What was your background prior to entering this challenge?
I’ve worked almost a decade in finance as a quantitative researcher and portfolio manager. I’ve also competed in several Kaggle contests, placing first in the Pfizer Volume Prediction Masters competition, sixth in the Merck Molecular Activity Challenge, and ninth in the Diabetic Retinopathy Detection.
