title: Is there a possibility to specify a minimum weight fraction for leaf nodes in XGBoost algorithms?
body: <p>I tried to implement a simple XGBoost algorithm and would like to specify a minimum weight fraction of my samples, that should be fulfilled in every leaf node. So far I only found the parameter min_child_weight, which specifies the minimum number of samples in a node. I would like to know if there is a way of how I can incorporate the weight of each sample here, since not each sample has weight=1?</p>
  <p>I would be super glad if someone can help here! Thank you :)</p>
  <p>Below you can find my code:</p>
  <pre><code>xg_r = xg.XGBRegressor(objective=&quot;reg:squarederror&quot;, n_estimators = 10, max_depth = 5, min_child_weight = 500000)
  xg_r.fit(X_train, y_train)
  xg.plot_tree(xg_r) 
  </code></pre>