code: def mean_abs_tree_shap(model, data):
      """mean(|TreeExplainer|)
      color = red_blue_circle(0.25)
      linestyle = solid
      """
  
      def f(X):
          v = TreeExplainer(model).shap_values(X)
          if isinstance(v, list):
              return [
                  np.tile(np.abs(sv).mean(0), (X.shape[0], 1))
                  for sv in v
              ]
          else:
              return np.tile(np.abs(v).mean(0), (X.shape[0], 1))
  
      return f
  
imports: import numpy
  import sklearn
  from ..None import DeepExplainer, GradientExplainer, KernelExplainer, LinearExplainer, SamplingExplainer, TreeExplainer, kmeans
  from ..explainers import other
  from .models import KerasWrap
label_desc: Use image node_id 9 for calling a global function with example usage: mean_abs_tree_shap(model, data) and returns: f, unknown, np