Weekly Champion Interview: Groot Team Shares Competition Strategies
The article introduces the Tencent Social Ads university algorithm contest weekly champion team Groot, details their background, and outlines their practical machine‑learning approach—including training set construction, XGBoost model selection, and feature engineering—while encouraging broader participation in such competitions.
After a week of intense competition, the Tencent Social Ads University Algorithm Contest announced its second weekly champion, the team Groot, consisting of three graduate students from University of Science and Technology of China.
In an interview, team captain wsss introduced the members and shared their background, noting prior experience with Kaggle’s Bosch Production Line Performance competition.
The team outlined their competition strategy: constructing an effective training set that mirrors the online environment while avoiding feature leakage; selecting XGBoost for its fast training feedback; focusing heavily on feature engineering by analyzing user interaction data and using tools such as xgbfir; and running the pipeline on a standard laptop without heavy optimization.
They reflected that winning the weekly champion involved some luck and limited experience, but emphasized the value of participating in such contests for learning, encouraging others to join and learn from winners’ solutions.
The article concludes with well‑wishes for future participants and provides links to the official contest website and registration page.
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