AI-900 Question 115
Single answerYou are tasked with building a machine learning model to predict the price of used cars based on a dataset. The dataset includes the following columns: 'Car_Model', 'Year', 'Mileage', 'Fuel_Type', and 'Price'. Which column(s) should be used as the label(s) for the model?
- A
'Car_Model'
- B
'Year'
- C
'Mileage'
- D
'Fuel_Type'
- E
'Price'
Show answer and explanation
Correct answer: E
Explanation
In a machine learning dataset, the label is the column or target variable that the model is trained to predict. In this scenario, the goal is to predict the 'Price' of a used car based on other factors (features) like 'Year', 'Mileage', and 'Fuel_Type'. Therefore, 'Price' is the label, and the other columns serve as features.
- A. Incorrect.
'Car_Model' represents the type or name of the car and is not a target variable for prediction. It is a feature, not a label.
- B. Incorrect.
'Year' indicates the manufacturing year of the car, which is an input feature that might affect the price, but it is not the label we are predicting.
- C. Incorrect.
'Mileage' refers to the distance a car has been driven, which is a feature that can influence the price but is not the target variable.
- D. Incorrect.
'Fuel_Type' specifies the type of fuel used by the car (e.g., petrol, diesel), which is another feature affecting the prediction but is not the label.
- E. Correct.
'Price' is the target variable we want to predict, making it the label in this dataset.