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meriva
3 years ago
6

You are given a data set with information from 1,000 high school students (of which the following is a part of the data) and ask

ed to build a machine learning solution that can predict the success of a student in completing a college degree. Which technique would be the best to use?Select one:a. Clusteringb. Text Analyticsc. Regressiond. Classification
Computers and Technology
1 answer:
serg [7]3 years ago
3 0

Answer:

Classification

Explanation:

Building a machine learning solution that can predict the success of a student in completing a college degree is a binary problem. There are two possible answer: success or not success.  

This brings us to a supervised machine learning problem, where one trains the technique with labeled data whether it is a success or not. Since the target variable is discrete (not continuous), classification technique has to be used.  

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These data provides the responses of 10 students in class A and in class B who were asked how many hours they slept lastThese da
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Answer:

Answer C

Explanation:

Class A Median: 4, 5, 6, 6, 7, 7, 7, 7, 8, 8

The Median of Class A is 7.

Class B Median: 5, 6, 6, 6, 7, 7, 7, 8, 8, 9

The Median of Class B is 7.

Class A Mean: 4 + 5 + 6 + 6 + 7 + 7 + 7 + 7 + 8 + 8 = 65

To find the mean, you add all of the numbers together, and divide the total by the amount of numbers. (There are ten numbers in the equation, so we divide 65 by 10.)

65/10 = 6.5, This means that the mean of Class A is 6.5

Class B Mean: 5 + 6 + 6 + 6 + 7 + 7 + 7 + 8 + 8 + 9 = 69

Do the same thing as last time, divide 69 by 10. (6.9)

The mean of class B is 6.9

Answer A and B are both incorrect, because the medians for both classes were the same.  Answer C is correct, because the mean of class B was 6.9 and the mean of Class A was 6.5

Answer D is also incorrect, 6.9 is 0.4 greater than 6.5

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