Exam AI-900 topic 1 question 170 discussion

RFM ( Recency, Frequency, Monetary) analysis is a proven marketing model for behavior based customer segmentation. It groups customers based on their transaction history - CORRECT ANSWER IS CLUSTERING

Clustering as per Bing AI

Clustering

segmentation = grouping and grouping is clustering

1. clustering https://learn.microsoft.com/en-us/training/modules/create-clustering-model-azure-machine-learning-designer/2-clustering-scenarios Clustering is a form of machine learning that is used to group similar items into clusters based on their features. For example, a researcher might take measurements of penguins, and group them based on similarities in their proportions.

RFM segmentation can be considered an example of Clustering. Clustering is an unsupervised learning method used for grouping data points, or objects that are similar to each other. In the case of RFM segmentation, customers are grouped based on their purchase behavior -- their Recency, Frequency, and Monetary value parameters. The goal is to divide customers into clusters where customers in the same group are more similar to each other than to those in other groups. RFM segmentation is not a form of Regression, as regression aims to predict a continuous outcome variable from one or more predictor variables. It also doesn't fit the definition of Classification, which is a supervised learning approach to predict a categorical outcome. Regularization is a technique used to prevent overfitting in regression and classification models, and it doesn't apply here as RFM segmentation is not about building a predictive model but rather a descriptive model for customer behavior.

here you need an unsupervised algorithm because you know inputs variables but don't know possible segments in output. you need to discover them. So correct answer is CLUSTERING.

CORRECT ANSWER IS CLUSTERING HINT SEGEMENT INTO GRPUP

RFM analysis does not involve training a machine learning model to predict a specific outcome, it does involve clustering data based on specific criteria, which makes it more of a form of clustering rather than classification. So would go for clustering.

Clustering.

For me the answer is clutering...