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))
B . Logistic regression
C . Support vector machine (SVM) with non-linear kernel
D . Single perceptron with tanh activation function
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
Reference: 1: https://docs.aws.amazon.com/sagemaker/latest/dg/svm.html
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