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telecom-churn-logistic_regression
RafaelPrime/telecom-churn-logistic_regression
telecom-churn-logistic_regression is a machine learning model from RafaelPrime. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Modelo de classificação binária para previsão de churn em clientes de telecomunicações.
Access
Public
Updated May 2, 2026
Repo size
8.4 KB
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.joblib8.4 KB · 77%
At a glance
- Access
- Public
- Created
- May 2, 2026
- Updated
- May 2, 2026
- SHA
- b9499f01
Model card
From the Hugging Face model README
telecom-churn-logistic_regression
Modelo de classificação binária para previsão de churn em clientes de telecomunicações.
Métricas (conjunto de teste — holdout 15%)
| Métrica | Valor |
|---|---|
| Recall(churn) | 0.7750 |
| F1 (weighted) | 0.7391 |
| ROC-AUC | 0.8221 |
| Accuracy | 0.7242 |
Uso
import joblib, pandas as pd
from huggingface_hub import hf_hub_download
model_path = hf_hub_download(repo_id="RafaelPrime/telecom-churn-logistic_regression", filename="logistic_regression.joblib")
prep_path = hf_hub_download(repo_id="RafaelPrime/telecom-churn-logistic_regression", filename="preprocessor.joblib")
model = joblib.load(model_path)
preprocessor = joblib.load(prep_path)
# X_raw: DataFrame com as colunas originais do dataset
X_proc = preprocessor.transform(X_raw)
pred = model.predict(X_proc)
- Languages
- pt
- Created
- May 2, 2026
- Updated
- May 2, 2026