Discover why Classification modeling might not be ideal for predicting spending habits of elite frequent flyer members. Explore better model choices for forecasting monetary amounts accurately.
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 how much money elite members of a frequent flyer program would be willing to spend on these new services.
You decided to implement Classification modeling.
Does this decision help you to achieve your goal?
A. Yes
B. No
Answer
B. No
Explanation
No, employing Classification modeling might not be the most suitable approach for predicting the monetary amount elite frequent flyer members are willing to spend on new premium cabin services. Classification models typically categorize data into predefined classes or categories rather than predicting continuous numerical values like monetary amounts. Regression modeling might be more fitting for predicting specific spending amounts.
Your task is to provide a regression prediction: supply a number value of the label. You can achieve this by creating a Regression model based on historical data.
Classification is a Machine Learning form that predicts a label’s probability to be a part of the class or a category based on historical data.
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