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Question 61 - MLS-C01 discussion

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A company wants to classify user behavior as either fraudulent or normal. Based on internal research, a Machine Learning Specialist would like to build a binary classifier based on two features: age of account and transaction month. The class distribution for these features is illustrated in the figure provided.

Based on this information which model would have the HIGHEST accuracy?

A.
Long short-term memory (LSTM) model with scaled exponential linear unit (SELL))
Answers
A.
Long short-term memory (LSTM) model with scaled exponential linear unit (SELL))
B.
Logistic regression
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B.
Logistic regression
C.
Support vector machine (SVM) with non-linear kernel
Answers
C.
Support vector machine (SVM) with non-linear kernel
D.
Single perceptron with tanh activation function
Answers
D.
Single perceptron with tanh activation function
Suggested answer: C

Explanation:

Based on the figure provided, the data is not linearly separable. Therefore, a non-linear model such as SVM with a non-linear kernel would be the best choice. SVMs are particularly effective in high-dimensional spaces and are versatile in that they can be used for both linear and non-linear data.Additionally, SVMs have a high level of accuracy and are less prone to overfitting1

References:1: https://docs.aws.amazon.com/sagemaker/latest/dg/svm.html

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asked 16/09/2024
Pawel Lenart
33 questions
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