Topic 1 Question 93

AWS Certified Machine Learning - Specialty

Topic 1 Question 93
A company wants to classify user behavior as either fraudulent or normal. Based on internal research, a machine learning specialist will build a binary classifier based on two features: age of account, denoted by x, and transaction month, denoted by y. The class distributions are illustrated in the provided figure. The positive class is portrayed in red, while the negative class is portrayed in black. Which model would have the HIGHEST accuracy?
- Linear support vector machine (SVM)
- Decision tree
- Support vector machine (SVM) with a radial basis function kernel
- Single perceptron with a Tanh activation function
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- Due to straight angles, I would choose Decision tree. See https://scikit-learn.org/stable/auto_examples/classification/plot_classifier_comparison.html#sphx-glr-auto-examples-classification-plot-classifier-comparison-py
  
  👍 23
  joep212021/09/21
- B - Decision tree - is not the best answer. If you use decision tree to do clustering, every time you need to partition the space into 2 parts. Hence you will split the space into 3*3. The red points in the center box and the black points will fall into the 8 boxes around it. The black points will be identified as 8 different classes.
  
  C is the correct answer. SVM with non-linear kernel is appropriate for non-linear clustering. Even if the shape is close to rectangular. SVM with non-linear kernel will be ale to approximate the rectangular boundary shape.
  
  👍 17
  SophieSu2021/09/22
- 正解だと思う選択肢: B
  This answer is decision tree due to the Square decision boundaries.
  
  👍 7
  vetaal2022/01/23
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