Datasets:

vivekkopthsd
/

churn-predict-data

license: mit
language:
  - en
task_categories:
  - tabular-classification
  - other
tags:
  - churn-prediction
  - customer-retention
  - survival-analysis
  - milp

Churn Predict — Data

Companion dataset for the churn_predict repository (Customer Churn Prediction & Retention-Budget Optimization).

Files

Path	Size	Description
`data/raw/ordered_open_ecommerce.parquet`	150 MB	Raw Open E-Commerce 1.0 purchase records (1,761,259 rows, 2018-01 .. 2023-03). Berke et al. 2024.
`models/artifacts.pkl`	197 MB	Fitted churn models, SHAP values, survival fits, and MILP results consumed by the Streamlit dashboard.

Why on the Hub

Both files exceed GitHub's 100 MB per-file hard limit, so they are hosted here and fetched at runtime by dashboard.py and build_dataset.py (via huggingface_hub.hf_hub_download).

Usage

from huggingface_hub import hf_hub_download

artifacts_path = hf_hub_download(
    repo_id="vivekkopthsd/churn-predict-data",
    filename="models/artifacts.pkl",
)

Source and License

Open E-Commerce 1.0 — Berke, A., Calacci, D., Mahari, R., Yabe, T., Larson, K. and Pentland, S. (2024). Open e-commerce 1.0, five years of crowdsourced U.S. Amazon purchase histories with user demographics. Scientific Data, 11. DOI 10.1038/s41597-024-03329-6. MIT (ungated).
models/artifacts.pkl — generated by train_models.py (all random seeds 42).
Ethics: only benign demographics and Amazon-usage survey items; sensitive survey items excluded.