code: def linear_shap_ind(model, data):
      """Linear SHAP (ind)"""
      return LinearExplainer(
          model, data, feature_dependence="independent"
      ).shap_values
  
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 2 for calling a global function with example usage: linear_shap_ind(model, data) and returns: LinearExplainer