advanced_model.py

# advanced_model.py
import lightgbm as lgb
import pandas as pd
import joblib

def train_advanced_model(dataframe, model_path="advanced_model.lgb"):
    X = dataframe.drop(columns=["success"])
    y = dataframe["success"]
    
    model = lgb.LGBMClassifier(
        n_estimators=300,
        learning_rate=0.05,
        max_depth=6,
        subsample=0.8,
        colsample_bytree=0.8,
        random_state=42
    )
    model.fit(X, y)
    joblib.dump(model, model_path)
    print("[AdvancedModel] Model trained and saved.")

def predict_token_advanced(features, model_path="advanced_model.lgb"):
    model = joblib.load(model_path)
    df = pd.DataFrame([features])
    proba = model.predict_proba(df)[0][1]
    return proba