Upload folder using huggingface_hub
Browse files- .gitattributes +2 -0
- .gitignore +2 -0
- data/customer_data.csv +301 -0
- implementation.ipynb +0 -0
- models/dbscan_model.pkl +3 -0
- models/gmm_model.pkl +3 -0
- models/hierarchical_model.pkl +3 -0
- models/kmeans_model.pkl +3 -0
- models/scaler.pkl +3 -0
- results/algorithm_comparison.csv +5 -0
- results/detailed_analysis.json +79 -0
- results/experiment_summary.json +44 -0
- visualizations/cluster_comparison.png +3 -0
- visualizations/optimal_k_analysis.png +3 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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visualizations/cluster_comparison.png filter=lfs diff=lfs merge=lfs -text
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visualizations/optimal_k_analysis.png filter=lfs diff=lfs merge=lfs -text
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.gitignore
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# Jupyter Notebook Checkpoints
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.ipynb_checkpoints/
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data/customer_data.csv
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1 |
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implementation.ipynb
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Algorithm,Silhouette Score,ARI vs True
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results/experiment_summary.json
ADDED
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{
|
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"experiment_date": "2025-07-15T20:53:15.486278",
|
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"type": "synthetic_customer_data",
|
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|
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|
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"Age",
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"Income"
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|
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"DBSCAN",
|
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"GMM"
|
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],
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"files_created": {
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"kmeans_model.pkl",
|
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"hierarchical_model.pkl",
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"dbscan_model.pkl",
|
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|
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"optimal_k_analysis.png",
|
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"cluster_comparison.png"
|
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],
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"results": [
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|
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"customer_data.csv"
|
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]
|
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},
|
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"key_findings": {
|
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"best_algorithm": "To be determined from results",
|
41 |
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"optimal_k": "Found using elbow method and silhouette analysis",
|
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"insights": "Customer segmentation reveals distinct spending patterns"
|
43 |
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}
|
44 |
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}
|
visualizations/cluster_comparison.png
ADDED
![]() |
Git LFS Details
|
visualizations/optimal_k_analysis.png
ADDED
![]() |
Git LFS Details
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