  In the free online game industry, churn prediction is an important research
topic. Reducing the churn rate of a game significantly helps with the success
of the game. Churn prediction helps a game operator identify possible churning
players and keep them engaged in the game via appropriate operational
strategies, marketing strategies, and/or incentives. Playtime related features
are some of the widely used universal features for most churn prediction
models. In this paper, we consider developing new universal features for churn
predictions for long-term players based on players' playtime.
