Discover why Clustering modeling might not suit predicting flyer preferences for airline services. Learn about the best model choices for precise predictions in airline customer analysis.
Table of Contents
Question
You work for a major airline. The airline is planning to implement new services for the premium cabin. You have been asked to predict whether elite members of a frequent flyer program favor these services or not.
You decided to implement Clustering modeling.
Does this decision help you to achieve your goal?
A. Yes
B. No
Answer
B. No
Explanation
No, Clustering modeling doesn’t suit this goal. Clustering is about grouping data based on similarities, not predicting specific outcomes. For predicting preferences, supervised learning models like classification or regression are more apt, not clustering.
Your task is to provide a classification prediction: answer the binary Yes or No question. You can achieve this by creating a Classification model based on the data from historical reviews.
The Clustering is a Machine Learning form that groups items based on some common properties.
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