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Question 162 - MLS-C01 discussion

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A Data Scientist is training a multilayer perception (MLP) on a dataset with multiple classes. The target class of interest is unique compared to the other classes within the dataset, but it does not achieve and acceptable ecall metric. The Data Scientist has already tried varying the number and size of the MLP's hidden layers, which has not significantly improved the results. A solution to improve recall must be implemented as quickly as possible.

Which techniques should be used to meet these requirements?

A.
Gather more data using Amazon Mechanical Turk and then retrain
Answers
A.
Gather more data using Amazon Mechanical Turk and then retrain
B.
Train an anomaly detection model instead of an MLP
Answers
B.
Train an anomaly detection model instead of an MLP
C.
Train an XGBoost model instead of an MLP
Answers
C.
Train an XGBoost model instead of an MLP
D.
Add class weights to the MLP's loss function and then retrain
Answers
D.
Add class weights to the MLP's loss function and then retrain
Suggested answer: D

Explanation:

The best technique to improve the recall of the MLP for the target class of interest is to add class weights to the MLP's loss function and then retrain. Class weights are a way of assigning different importance to each class in the dataset, such that the model will pay more attention to the classes with higher weights. This can help mitigate the class imbalance problem, where the model tends to favor the majority class and ignore the minority class. By increasing the weight of the target class of interest, the model will try to reduce the false negatives and increase the true positives, which will improve the recall metric. Adding class weights to the loss function is also a quick and easy solution, as it does not require gathering more data, changing the model architecture, or switching to a different algorithm.

References:

AWS Machine Learning Specialty Exam Guide

AWS Machine Learning Training - Deep Learning with Amazon SageMaker

AWS Machine Learning Training - Class Imbalance and Weighted Loss Functions

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asked 16/09/2024
Matthew Walsh
31 questions
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