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Question 126 - DP-100 discussion

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You are evaluating a completed binary classification machine learning model.

You need to use the precision as the evaluation metric.

Which visualization should you use?

A.
Violin plot
Answers
A.
Violin plot
B.
Gradient descent
Answers
B.
Gradient descent
C.
Box plot
Answers
C.
Box plot
D.
Binary classification confusion matrix
Answers
D.
Binary classification confusion matrix
Suggested answer: D

Explanation:

Incorrect Answers:

A: A violin plot is a visual that traditionally combines a box plot and a kernel density plot.

B: Gradient descent is a first-order iterative optimization algorithm for finding the minimum of a function. To find a local minimum of a function using gradient descent, one takes steps proportional to the negative of the gradient (or approximate gradient) of the function at the current point.

C: A box plot lets you see basic distribution information about your data, such as median, mean, range and quartiles but doesn't show you how your data looks throughout its range.

Reference:

https://machinelearningknowledge.ai/confusion-matrix-and-performance-metrics-machine-learning/

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asked 02/10/2024
Ahmed Khan
47 questions
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