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Regular version of the site

Student
Title
Supervisor
Faculty
Educational Programme
Final Grade
Year of Graduation
Timur Kadirov
Attribution of Customer's Actions Based on Machine Learning Approach
Data Science
(Master’s programme)
2018
Multichannel attribution model based on gradient boosting over trees is proposed, which was compared with the state of the art models: bagged logistic regression, markov chains approach, shapley value. Experiments on digital advertising datasets showed that the proposed model is better than the solutions considered by ROC AUC metric.

In addition, the problem of probability prediction of conversion by the consumer using the ensemble of the analyzed algorithms was solved, the meta-features obtained were enriched with consumers and offline activities of the advertising campaign data.

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