Commit From AutoTrain

.gitattributes

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README.md

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+---
+tags:
+- autotrain
+- tabular
+- classification
+- tabular-classification
+datasets:
+- reachosen/autotrain-data-palv1
+co2_eq_emissions:
+  emissions: 1.2993450618764815
+---
+
+# Model Trained Using AutoTrain
+
+- Problem type: Binary Classification
+- Model ID: 76806140361
+- CO2 Emissions (in grams): 1.2993
+
+## Validation Metrics
+
+- Loss: 0.192
+- Accuracy: 0.919
+- Precision: 1.000
+- Recall: 0.667
+- AUC: 0.978
+- F1: 0.800
+
+## Usage
+
+```python
+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)
+
+```

config.json

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+{"features": ["Age", "Comorbidities", "ICU Admission", "ICU Stay Duration", "Cardiac Arrest Event", "ICH Intubation", "Acute on Chronic Exacerbations", "HCPOA Status", "Family Disagreement", "Non-Beneficial Care Perception", "Surprise Question Outcome", "ICU Stay >1 Month", "MSOF >3 Systems", "Hospital Death Expected", "Advanced Dementia", "Palliative Care Outpatient", "Active Metastatic Disease", "Unnamed: 18", "Unnamed: 19", "Unnamed: 20", "Unnamed: 21", "Unnamed: 22"], "targets": ["target"], "model_type": "xgboost", "target_mapping": {"N": 0, "Y": 1}}

model.joblib

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