Abstract
The click-through rate is one of the main indicators based of which decisions are made in online advertising. A generalized approach to forecasting the click-through rate is proposed, taking into account the specifics of the industry data and using appropriate methods of processing categorical data and tree-based classification models. The simulation results can be used in the subsequent stages of analysis of advertising campaigns.
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