You have a data-set of house prices. One feature in the data belongs to the number of bedrooms. It ranges from 0 to 10 with most of the houses having 2 and 3 bedrooms. You need to remove the outlier in this data-set to build a model later on. Which approach is better?

let's assume 0 stands for not-rainy and 1 stands for rainy days. A business of a large chain ice cream store is using this model to close some branches if it is predicted to rain. A night before, based on model prediction, employees receive an email if they need to show up tomorrow at work or not. The company is already well-known and doesn't need to acquire more customers. Their focus for now is to save costs and not open the store, when there is no customer due to the rain. With this background, which performance metrics will you choose?

(10 Points)

accuracy

precision

recall

F1_score