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DY0-001 · Question #69

A data scientist has built an image recognition model that distinguishes cars from trucks. The data scientist now wants to measure the rate at which the model correctly identifies a car as a car…

The correct answer is A. Confusion matrix. A confusion matrix directly shows true positives (cars correctly identified) and false positives (trucks misidentified as cars), giving you exactly the rates you're interested in.

Modeling, Analysis, and Outcomes

Question

A data scientist has built an image recognition model that distinguishes cars from trucks. The data scientist now wants to measure the rate at which the model correctly identifies a car as a car versus when it misidentifies a truck as a car. Which of the following would best convey this information?

Options

  • AConfusion matrix
  • BAUC/ROC curve
  • CBox plot
  • DCorrelation plot

How the community answered

(49 responses)
  • A
    84% (41)
  • B
    4% (2)
  • C
    2% (1)
  • D
    10% (5)

Explanation

A confusion matrix directly shows true positives (cars correctly identified) and false positives (trucks misidentified as cars), giving you exactly the rates you're interested in.

Topics

#confusion matrix#true positive rate#false positive rate#classification metrics

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