ttungl / channel-attribution-model Goto Github PK

This project forked from jeremite/channel-attribution-model

An attention-based Recurrent Neural Net multi-touch attribution model in a supervised learning fashion of predicting if a series of events leads to conversion (purchase). The trained model can also assign credits to channels. The model also incorporates user-context information, such as user demographics and behavior, as control variables to reduce the estimation biases of media effects.