Topic 1 Question 25
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 recall with respect to the fraudulent class?Decision tree
Linear support vector machine (SVM)
Naive Bayesian classifier
Single Perceptron with sigmoidal activation function
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C is the correct answer because gaussian naive Bayes can do this nicely.
👍 12E_aws2021/10/29Answer should be A:. B: LINEAR SVM is a linear classifier -> All of these have a linear decision boundary (so it's just a line y = mx+b). This leads to a bad recall and so A must be the right choice.
👍 6blubb2021/10/23Answer is correct. It has to be C. Check out there: https://stackoverflow.com/questions/21468469/logistic-regression-and-naive-bayes-for-this-dataset The variance in yellow is smaller and bigger in black. NB can make a perfect prediction.
On the other hand, tree models are known for inefficiency on round decision boundary, since you have to got thousand small rectangles to approximate the round shape.
👍 5INNN2021/10/24
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