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Exam AWS Certified Machine Learning - Specialty topic 1 question 24 discussion

Exam question from Amazon's AWS Certified Machine Learning - Specialty
Question #: 24
Topic #: 1
[All AWS Certified Machine Learning - Specialty Questions]

A Machine Learning Specialist trained a regression model, but the first iteration needs optimizing. The Specialist needs to understand whether the model is more frequently overestimating or underestimating the target.
What option can the Specialist use to determine whether it is overestimating or underestimating the target value?

  • A. Root Mean Square Error (RMSE)
  • B. Residual plots
  • C. Area under the curve
  • D. Confusion matrix
Show Suggested Answer Hide Answer
Suggested Answer: B 🗳️
by DonaldCMLIN at Nov. 16, 2019, 4:20 a.m.
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vetal
Highly Voted 2 years, 1 month ago
RMSE says about the error value but not the sign of error. The question is to find whether the model overestimates or underestimates - I guess residual plots clearly show that answer B
upvoted 37 times
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rsimham
Highly Voted 2 years, 1 month ago
Answer is B. Residual plot distribution indicates over or under-estimations
upvoted 14 times
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JonSno
Most Recent 2 months, 2 weeks ago
Selected Answer: B
A residual plot helps determine whether a regression model is overestimating or underestimating the target value. Residual = Actual Value - Predicted Value Positive residual → The model underestimated the target. Negative residual → The model overestimated the target. By plotting residuals, the Machine Learning Specialist can see patterns that indicate bias: More positive residuals → The model is underestimating. More negative residuals → The model is overestimating. Randomly scattered residuals around zero → The model is well-calibrated.
upvoted 1 times
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Valcilio
7 months, 4 weeks ago
Selected Answer: B
Residual plots shows mistake by mistake!
upvoted 1 times
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vetaal
1 year, 9 months ago
Selected Answer: B
B - Residual plots it is - https://docs.aws.amazon.com/machine-learning/latest/dg/regression-model-insights.html
upvoted 4 times
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felbuch
2 years ago
Residual Plots (B). AUC and Confusion Matrices are used for classification problems, not regression. And RMSE does not tell us if the target is being over or underestimated, because residuals are squared! So we actually have to look at the residuals themselves. And that's B.
upvoted 7 times
cnethers
1 year, 12 months ago
Root Mean Square Error (RMSE) is the standard deviation of the residuals (prediction errors). Residuals are a measure of how far from the regression line data points are; RMSE is a measure of how spread out these residuals are. In other words, it tells you how concentrated the data is around the line of best fit. Root mean square error is commonly used in climatology, forecasting, and regression analysis to verify experimental results. 1) Squaring the residuals. 2) Finding the average of the residuals. 3) Taking the square root of the result.
upvoted 3 times
cnethers
1 year, 12 months ago
Residual Plots (B). would have to be my answer
upvoted 1 times
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Thai_Xuan
2 years ago
residual plot https://docs.aws.amazon.com/machine-learning/latest/dg/regression-model-insights.html
upvoted 5 times
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syu31svc
2 years ago
https://stattrek.com/statistics/dictionary.aspx?definition=residual%20plot#:~:text=A%20residual%20plot%20is%20a,nonlinear%20model%20is%20more%20appropriate. Answer is B
upvoted 2 times
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Antriksh
2 years ago
without a second thought residual plot
upvoted 2 times
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qururu
2 years ago
The answer is B. Refer to Exercise 7.2.1.A https://stats.libretexts.org/Bookshelves/Introductory_Statistics/Book%3A_OpenIntro_Statistics_(Diez_et_al)./07%3A_Introduction_to_Linear_Regression/7.02%3A_Line_Fitting%2C_Residuals%2C_and_Correlation
upvoted 1 times
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C10ud9
2 years ago
Residual plot it is Option B
upvoted 1 times
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roytruong
2 years ago
Residual plot
upvoted 2 times
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deep_n
2 years ago
B is the correct answer!!!! RMSE has the S in it that is square... that vanishes the above below factor of the prediction. Answers C and D are for other type of problems
upvoted 4 times
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swagy
2 years ago
It should be B. The residual plot will be give whether the target value is overestimated or underestimated.
upvoted 1 times
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Jayraam
2 years ago
Answer is C. https://www.youtube.com/watch?v=MrjWcywVEiU
upvoted 2 times
ExamTaker123456789
2 years ago
Answer is B. Your vid shows a technique that is useful for defining integrals and has NOTHING to do linear regression. Also, it over-/underestimates the area under the curve, NOT the target value.
upvoted 2 times
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cloud_trail
1 year, 12 months ago
Good grief, AUC is used for classification not regression.
upvoted 1 times
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PRC
2 years ago
B..Residual helps to find out whether the model is underestimating or overestimating
upvoted 3 times
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AKT
2 years, 1 month ago
answer is B
upvoted 2 times
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