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pbc_complication_model

Scikit-learn
Joblib
RandomForestClassifier
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pbc_complication_model
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{
    "model_type": "RandomForestClassifier",
    "expected_features": [
        "age", 
        "sex", 
        "serum_bilirubin", 
        "serum_cholesterol", 
        "albumin", 
        "alkaline_phosphatase", 
        "SGOT", 
        "platelets", 
        "prothrombin_time"
    ],
    "categorical_features": [
        "drug", 
        "sex", 
        "presence_of_ascites", 
        "presence_of_hepatomegaly", 
        "presence_of_spiders", 
        "presence_of_edema"
    ],
    "model_parameters": {
        "criterion": "entropy",
        "max_features": 0.1,
        "min_samples_split": 8,
        "min_samples_leaf": 6,
        "bootstrap": true
    },
    "version": "1.0",
    "preprocessing": {
        "numerical": "median imputation and scaling",
        "categorical": "one-hot encoding",
        "ordinal": "label encoding"
    }
}