A city wants to monitor its air quality to address the consequences of air pollution. A Machine Learning Specialist needs to forecast the air quality in parts per million of contaminates for the next 2 days in the city. As this is a prototype, only daily data from the last year is available. Which model is MOST likely to provide the best results in Amazon SageMaker?
A) Use the Amazon SageMaker k-Nearest-Neighbors (kNN) algorithm on the single time series consisting of the full year of data with a predictor_type of regressor . Use the Amazon SageMaker k-Nearest-Neighbors (kNN) algorithm on the single time series consisting of the full year of data with a predictor_type of regressor .
B) Use Amazon SageMaker Random Cut Forest (RCF) on the single time series consisting of the full year of data.
C) Use the Amazon SageMaker Linear Learner algorithm on the single time series consisting of the full year of data with a predictor_type of regressor . Use the Amazon SageMaker Linear Learner algorithm on the single time series consisting of the full year of data with a
D) Use the Amazon SageMaker Linear Learner algorithm on the single time series consisting of the full year of data with a predictor_type of classifier . classifier

Question

Quizplus · Accepted Answer

The Linear Learner algorithm with a regressor predictor type is suitable for time series forecasting tasks, as it can model the relationship between time and the air quality measurements to predict future values.

A City Wants to Monitor Its Air Quality to Address