Click prediction boosting via Bayesian hyperparameter optimization based ensemble learning pipelines. (arXiv:2206.03592v2 [cs.LG] UPDATED)

Online travel agencies (OTA's) advertise their website offers on meta-search
bidding engines. The problem of predicting the number of clicks a hotel would
receive for a given bid amount is an important step in the management of an
OTA's advertisement campaign on a meta-search engine, because bid times number
of clicks defines the cost to be generated. Various regressors are ensembled in
this work to improve click prediction performance. Following the preprocessing
procedures, the feature set is divided into train …

arxiv bayesian boosting click ensemble learning lg optimization pipelines prediction