PMG Group Malaysia is a Chinese group of companies best known for its book retailing and online retailing services as well as being involved in the printing, publishing and supply of books and library services in China and Taiwan. PMG Bookstores currently has 65 outlets in China and 6 in Taiwan.
The management team has been strengthened to improve its customer service and its range of books. Steps have been taken to upgrade the computer system to improve the efficiency of PMG Bookstores` inventory control and customer service delivery. PMG Bookstores continues to seek choice locations for new outlets in China. PMG Group hosts their web application to sell the books and improve web sales. The application is built on AWS running out EC2 and RDS.
PMG Group understand recently an avalanche of negative reviews about some of the books released in market and is interested to know whether the reviews provided are by customers or bots. PMG identifies AWS ML to provide a quick turnaround. Please advice. Select 3 options.

Answer options:

A.Amazon ML uses logistic regression algorithm through Binary classification to solve the business problem
B.Amazon ML uses multi-nominal logistic regression algorithm through multi-class classification to solve the business problem
C.Amazon ML uses linear regression algorithm through regression model to solve the business problem
D.Amazon ML uses Area Under the (Receiver Operating Characteristic) Curve (AUC) to provide accuracy of the model
E.Cross-validation is a technique for evaluating ML models by training several ML models on subsets of the available input data to detect overfitting which eventually fails to generalize the pattern
F.Amazon ML uses macro-average F1 score to provide accuracy of the model
G.Amazon ML uses standard root mean square error (RMSE) metric to provide accuracy of the model

Answer : A,D, E
Option A is correct -ML models for binary classification problems predict a binary outcome
https://docs.aws.amazon.com/machine-learning/latest/dg/types-of-ml-models.html
Option B is incorrect - ML models for multiclass classification problems allow you to generate predictions for multiple classes (predict one of more than two outcomes).
https://docs.aws.amazon.com/machine-learning/latest/dg/types-of-ml-models.html
Option C is incorrect - ML models for regression problems predict a numeric value.
https://docs.aws.amazon.com/machine-learning/latest/dg/types-of-ml-models.html
Option D is correct - Amazon ML provides an industry-standard accuracy metric for binary classification models called Area Under the (Receiver Operating Characteristic) Curve (AUC).
https://docs.aws.amazon.com/machine-learning/latest/dg/binary-model-insights.html
Option E is correct - Cross-validation is a technique for evaluating ML models by training several ML models on subsets of the available input data and evaluating them on the complementary subset of the data. Use cross-validation to detect overfitting
https://docs.aws.amazon.com/machine-learning/latest/dg/cross-validation.html
Option F is incorrect - The macro-average F1 score is used to evaluate the predictive accuracy of a multiclass metric.
https://docs.aws.amazon.com/machine-learning/latest/dg/multiclass-model-insights.html
Option G is incorrect -For linear regression tasks, Amazon ML uses the industry standard root mean square error (RMSE) metric.
https://docs.aws.amazon.com/machine-learning/latest/dg/regression-model-insights.html