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Data Mining Graded Quiz • 10 min(Data science) (ibm) quiz 2 (Coursera)

Congratulations! You passed!
TO PASS 80% or higher
GRADE
80%

Data Mining

LATEST SUBMISSION GRADE
80%
1.Question 1
According to the reading, the output of a data mining exercise largely depends on:
Correct
Correct.
1 / 1 point
2.Question 2
When data are missing in a systematic way, you can simply extrapolate the data or impute the missing data by filling in the average of the values around the missing data.
Correct
Correct. When data are missing in a systematic way, you should determine the impact of missing data on the results and whether missing data can be excluded from the analysis.
1 / 1 point
3.Question 3
Prior Variable Analysis and Principal Component Analysis are both examples of a data reduction algorithm.
Correct
Correct. Prior Variable Analysis is not a data reduction algorithm.
1 / 1 point
4.Question 4
After the data are appropriately processed, transformed, and stored, machine learning and non-parametric methods are a good starting point for data mining.
Correct
Correct.
1 / 1 point
5.Question 5
“Formal evaluation could include testing the predictive capabilities of the models on observed data to see how effective and efficient the algorithms have been in reproducing data.” This is known as:
Incorrect
Incorrect.

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