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CustomerSegmentation-kmeans
Marsill/CustomerSegmentation-kmeans
CustomerSegmentation-kmeans is a machine learning model from Marsill. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
This repository contains a trained K-Means clustering model for customer segmentation, along with a scaler to preprocess input features.
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Public
Updated Sep 23, 2025
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At a glance
- License
- mit
- Access
- Public
- Created
- Sep 23, 2025
- Updated
- Sep 23, 2025
- SHA
- d855518d
Model card
From the Hugging Face model README
Customer Segmentation Model
This repository contains a trained K-Means clustering model for customer segmentation, along with a scaler to preprocess input features.
Files
kmeans_model.pkl– Trained K-Means modelscaler.pkl– StandardScaler used to normalize features before clustering
Description
The model segments customers into two clusters:
| Cluster | Label | Description |
|---|---|---|
| 0 | High Spender | Customers with high sales and profit |
| 1 | Occasional Buyer | Customers with lower or occasional purchases |
The model was trained on the Superstore dataset.
Input Features
To predict the cluster of a customer, the model expects a dictionary with the following keys:
TotalSales– Total sales of the customerAvgSales– Average sales per orderTotalProfit– Total profit from the customerAvgProfit– Average profit per orderTotalQuantity– Total quantity purchasedAvgDiscount– Average discount received (0-1)
- License
- mit
- Created
- Sep 23, 2025
- Updated
- Sep 23, 2025