Which of the following modeling techniques should the Specialist use1?

A Machine Learning Specialist is building a supervised model that will evaluate customers’ satisfaction with their mobile phone service based on recent usage. The model’s output should infer whether or not a customer is likely to switch to a competitor in the next 30 days.

Which of the following modeling techniques should the Specialist use1?
A . Time-series prediction
B . Anomaly detection
C . Binary classification
D . Regression

View Answer

Answer: C

Explanation:

The modeling technique that the Machine Learning Specialist should use is binary classification. Binary classification is a type of supervised learning that predicts whether an input belongs to one of two possible classes. In this case, the input is the customer’s recent usage data and the output is whether or not the customer is likely to switch to a competitor in the next 30 days. This is a binary outcome, either yes or no, so binary classification is suitable for this problem. The other options are not appropriate for this problem. Time-series prediction is a type of supervised learning that forecasts future values based on past and present data. Anomaly detection is a type of unsupervised learning that identifies outliers or abnormal patterns in the data. Regression is a type of supervised learning that estimates a continuous numerical value based on the input features.

References: Binary Classification, Time Series Prediction, Anomaly Detection, Regression