AI-900 Question 111
Select 4You are tasked with creating a machine learning model to predict house prices using a dataset. The dataset includes the following columns: 'SquareFootage', 'NumberOfBedrooms', 'Neighborhood', and 'Price'. Which of the following are features, and which is the label in this dataset?
- A
'SquareFootage' is a feature
- B
'NumberOfBedrooms' is a feature
- C
'Neighborhood' is a feature
- D
'Price' is a feature
- E
'Price' is the label
Show answer and explanation
Correct answers: A, B, C, E
Explanation
In supervised machine learning, features are the input variables used to make predictions, while the label is the target variable we aim to predict. In this dataset, 'SquareFootage', 'NumberOfBedrooms', and 'Neighborhood' are the features providing input data, and 'Price' is the label that the model will predict.
- A. Correct.
'SquareFootage' is a feature because it is an input variable used to help predict the target value.
- B. Correct.
'NumberOfBedrooms' is a feature because it is an input variable that contributes information to the model.
- C. Correct.
'Neighborhood' is a feature because it is another input variable providing contextual data for the model.
- D. Incorrect.
'Price' is not a feature, as it represents the target value we are trying to predict.
- E. Correct.
'Price' is the label because it is the output variable (target) the model is trained to predict.