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import xgboost as xgb | |
from utils.dataprocess import create_features | |
import streamlit as st | |
def xgboost(X, y, max_depth, learning_rate, n_estimators): | |
model = xgb.XGBRegressor(n_estimators=n_estimators, learning_rate=learning_rate, max_depth=max_depth) | |
model.fit(X, y) | |
return model |