You are performing a market basket analysis where there are over 5 million different types of electronic components for sale, and shopping carts often contain over 100 components. You have the data, but there are too many components to check all combinations, so the next step is to identify the most frequently-used combinations. Which machine learning technique would be most relevant in this scenario? (Select one) A. Decision Tree B. k-Means clustering C. Support Vector Machine D. FP-Growth

EBK ELECTRICAL WIRING RESIDENTIAL
19th Edition
ISBN:9781337516549
Author:Simmons
Publisher:Simmons
Chapter29: Service-entrance Calculations
Section: Chapter Questions
Problem 3R: a. What is the ampere rating of the circuits that are provided for the small-appliance loads? _____...
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Topic: Unsupervised Techniques
You are performing a market basket analysis where there are over 5 million different types of electronic components for sale, and shopping carts often contain over 100 components. You
have the data, but there are too many components to check all combinations, so the next step is to identify the most frequently-used combinations. Which machine learning technique would
be most relevant in this scenario? (Select one)
A. Decision Tree
B. k-Means clustering
C. Support Vector Machine
D. FP-Growth
Transcribed Image Text:Topic: Unsupervised Techniques You are performing a market basket analysis where there are over 5 million different types of electronic components for sale, and shopping carts often contain over 100 components. You have the data, but there are too many components to check all combinations, so the next step is to identify the most frequently-used combinations. Which machine learning technique would be most relevant in this scenario? (Select one) A. Decision Tree B. k-Means clustering C. Support Vector Machine D. FP-Growth
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