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IEEE/ICACT20220017 Question.1 Questioner: 211120098@fzu.edu.cn 2022-02-14 오전 3:50:51	IEEE/ICACT20220017 Answer.1 Answer by Auhor patrick.hosein@sta.uwi.edu 2022-02-14 오전 3:50:51
Why you chose a relatively simple model like logistic regression model and what are its benefits？	I tested many different models such as decision tree, support vector machine (svm) and naive bayes classifier, and I even included more complex models in my testing like random forest and gradient boosting algorithm. However, the accuracy metric obtained from these models were either lower or only marginally better than the logistic regression. I chose to use the logistic regression model because it offers the benefit of interpretability. Remember, the model is being used to help the Account Managers select the best product recommendation to upsell to the customers. The managers would most probably want to know the main reasons why the particular upsell product is being recommended, so they can use this information in developing a relevant and persuasive strategy when targeting the customers. With a logistic regression, it is easy to discover which variables impact on the recommended output made by the model, and the weight of this impact. This can be easily interpreted using the coefficients of the regressors in the model.

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