2. Imagine you are given the task to predict the educational qualification of each person using their demographic data with the following attributes: (1) Annual Income (real-valued), (2) Income Tax filed (real-valued), (3) Age (integer), (4) State of residence in US (categorical), (5) Gender (categorical), (6) House Owner or not (Boolean), and (7) Height (in inches). Assume the target classes are (a) college degree and (b) without a college degree. Also, assume that the fraction of the population that has a

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Chapter3: Performing Calculations With Formulas And Functions
Section3.1: Formulas And Functions
Problem 8QC
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Need help with this data mining question regarding decision trees

2. Imagine you are given the task to predict the educational qualification of each person using their
demographic data with the following attributes: (1) Annual Income (real-valued), (2) Income Tax filed
(real-valued), (3) Age (integer), (4) State of residence in US (categorical), (5) Gender (categorical), (6)
House Owner or not (Boolean), and (7) Height (in inches). Assume the target classes are (a) college
degree and (b) without a college degree. Also, assume that the fraction of the population that has a
college degree is roughly equal to the fraction that does not have a college degree. State two strengths
and one weakness of decision trees for this task.
Transcribed Image Text:2. Imagine you are given the task to predict the educational qualification of each person using their demographic data with the following attributes: (1) Annual Income (real-valued), (2) Income Tax filed (real-valued), (3) Age (integer), (4) State of residence in US (categorical), (5) Gender (categorical), (6) House Owner or not (Boolean), and (7) Height (in inches). Assume the target classes are (a) college degree and (b) without a college degree. Also, assume that the fraction of the population that has a college degree is roughly equal to the fraction that does not have a college degree. State two strengths and one weakness of decision trees for this task.
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