2. A Machine Learning Specialist is training a logistic regression model for predicting hotel booking cancellations. The Specialist hopes to develop the best version of the model with the optimal classification threshold score. For this reason, he needs to evaluate how various threshold settings affect model performance. Which approach should the Specialist apply?Evaluate the model using recallEvaluate the model using the Root Mean Square Error (RMSE).Evaluate the model using the L1 norm.Evaluate the model using the Receiver Operating Characteristic Curve (ROC)Evaluate the model using a scatter plot graph.
Question
- A Machine Learning Specialist is training a logistic regression model for predicting hotel booking cancellations. The Specialist hopes to develop the best version of the model with the optimal classification threshold score. For this reason, he needs to evaluate how various threshold settings affect model performance. Which approach should the Specialist apply?Evaluate the model using recallEvaluate the model using the Root Mean Square Error (RMSE).Evaluate the model using the L1 norm.Evaluate the model using the Receiver Operating Characteristic Curve (ROC)Evaluate the model using a scatter plot graph.
Solution
The Specialist should evaluate the model using the Receiver Operating Characteristic Curve (ROC). The ROC curve is a graphical representation that illustrates the diagnostic ability of a binary classifier system as its discrimination threshold is varied. It can help the Specialist to choose the optimal threshold for the logistic regression model. This method is particularly useful when the classes are somewhat imbalanced, like in the case of predicting hotel booking cancellations.
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