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Diabetes_model
M-Ahmad-Abid/Diabetes_model
Diabetes_model is a tabular classification model from M-Ahmad-Abid. Use it for the tabular classification task on the model card, and read the license before you ship it in a product. It is set up for transformers.
- Problem type: Binary Classification - Model ID: 53980126976 - CO2 Emissions (in grams): 0.9262
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Repo size
431 KB
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.joblib431 KB · 99%
At a glance
- Task
- Tabular Classification
- Library
- transformers
- Model type
- xgboost
- Access
- Public
- Created
- Apr 29, 2023
- Updated
- Apr 29, 2023
- SHA
- 06229ed8
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 53980126976
- CO2 Emissions (in grams): 0.9262
Validation Metrics
- Loss: 0.459
- Accuracy: 0.773
- Precision: 0.667
- Recall: 0.704
- AUC: 0.852
- F1: 0.685
Usage
import json
import joblib
import pandas as pd
model = joblib.load('model.joblib')
config = json.load(open('config.json'))
features = config['features']
# data = pd.read_csv("data.csv")
data = data[features]
data.columns = ["feat_" + str(col) for col in data.columns]
predictions = model.predict(data) # or model.predict_proba(data)
- Task
- Tabular Classification
- Library
- transformers
- Type
- xgboost
- Created
- Apr 29, 2023
- Updated
- Apr 29, 2023