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Exam DP-100 topic 2 question 41 discussion

Actual exam question from Microsoft's DP-100

Question #: 41
Topic #: 2

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
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You are analyzing a numerical dataset which contains missing values in several columns.
You must clean the missing values using an appropriate operation without affecting the dimensionality of the feature set.
You need to analyze a full dataset to include all values.
Solution: Calculate the column median value and use the median value as the replacement for any missing value in the column.
Does the solution meet the goal?

A. Yes
B. No

Show Suggested Answer

Suggested Answer: A 🗳️

by amarques at Aug. 2, 2019, 11:09 a.m.

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Aleem

Highly Voted 4 years, 1 month ago

"You need to analyze a full dataset" just means you can't drop the rows or the columns. Replacing missing data with the median may increase the cardinality but dimensionality is only increased by adding new feature columns. Median replacement is a valid method in this case. The answer should be "Yes".

upvoted 34 times

TheYazan

3 years, 3 months ago

I guess because they mentioned "appropriate" which is vague but it might be the case

upvoted 2 times

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amarques

Highly Voted 5 years, 10 months ago

In the reference you mentioned it's not explicit that you can only use MICE. There's any reason because we cannot use median? Thank you

upvoted 14 times

NaishinMatiri

4 years, 2 months ago

I think the answer should ONLY be the Mean. Since there are missing values in many columns and MICE uses other columns to calculate the value. Trying to calculate values where the other columns also have missing values could alter the result.

upvoted 4 times

andre999

4 years ago

You can also use Median for numerical values, as stated in the exercice.

upvoted 3 times

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jefimija

Most Recent 8 months, 2 weeks ago

if values are missing in the entire column, how do you calculate the median?

upvoted 1 times

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haby

1 year, 6 months ago

B for sure. Median is only available if the columns/rows are numeric or ordinal, if they are categorical or even string, we have to use Mode or other methods.

upvoted 1 times

Anjiiiiiii

1 year ago

The question says it's a numerical dataset.

upvoted 2 times

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Ahmed_Gehad

1 year, 11 months ago

Selected Answer: A

The solution meets the goal because it uses an appropriate operation to clean the missing values without affecting the dimensionality of the feature set. The median value is a good choice for imputing missing values because it is not affected by outliers. Additionally, the median value does not affect the dimensionality of the feature set because it is a single value.

upvoted 1 times

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snegnik

2 years, 1 month ago

I think B is True. Median replacement "analyze" only one column, but MICE method use all columns for one. Also we can use Probablistic PCA mothod.

upvoted 2 times

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MarinaMijailovic

2 years, 1 month ago

If columns are numeric then yes, otherwise no. The problem is we dont have that information.

upvoted 1 times

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swatidorge1010

2 years, 1 month ago

Selected Answer: A

Please change answer or justify

upvoted 1 times

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swatidorge1010

2 years, 1 month ago

Selected Answer: B

Answer : B As its not mentioned all columns have numeric values.

upvoted 2 times

snegnik

2 years, 1 month ago

It is mentioned "You are analyzing a numerical dataset"

upvoted 2 times

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ajay0011

2 years, 2 months ago

Selected Answer: A

Yes is the answer, please change it

upvoted 1 times

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Edriv

2 years, 6 months ago

Agree A

upvoted 1 times

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jlopezfelizzola

2 years, 9 months ago

Selected Answer: A

Should be A

upvoted 3 times

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FU_User

3 years, 1 month ago

Selected Answer: A

It is correct as it doesn't add or drop columns. Also "You need to analyze a full dataset" can either mean that the algorithm should take the full existing dataset into account when replacing values (which this one does) or that no existing data should be deleted (median does not delete anything)

upvoted 3 times

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VEDPRASAD

3 years, 3 months ago

Selected Answer: A

In an existing project we did median, with clustered dataset. so median works

upvoted 2 times

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David_Tadeu

3 years, 3 months ago

Selected Answer: A

Applying the mentioned method to the following dataset 1 | 5 | - | - | 7 | 3 | - | 0 | 2 | 2 | 7 | 4 | 2 | 6 | 9 | - | 2 | - | 3 | - | - | - | 7 | - | would lead to 1 | 4 | 4 | 4 | 7 | 3 | 2 | 0 | 2 | 2 | 7 | 4 | 2 | 6 | 9 | 4 | 2 | 4 | 3 | 5 | 5 | 5 | 7 | 5 | Hence - missing data cleaned - dimensionality preserved

upvoted 4 times

David_Tadeu

3 years, 3 months ago

oops the entry (1,2) is meant to be a 5 in the dataset below

upvoted 1 times

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synapse

3 years, 3 months ago

Selected Answer: A

Copying a good answer: "You need to analyze a full dataset" just means you can't drop the rows or the columns. Replacing missing data with the median may increase the cardinality but dimensionality is only increased by adding new feature columns. Median replacement is a valid method in this case. The answer should be "Yes"

upvoted 4 times

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mikosann

3 years, 9 months ago

I think the answer is correct. Filling missing values with mean/median is a highly used method. It works on each column separately and independently. And it only replaces the missing values, doesn't add any new columns or new rows to the dataset which means it doesn't effect dimensions. Taking the mean/median of the column and replacing missing values is one of the beginner data science topics. MICE can be a better method but this doesn't mean the answer is wrong.

upvoted 4 times

mikosann

3 years, 9 months ago

I mean the solution is correct. Not the answer.

upvoted 3 times

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