class_docstr: State pattern attached to SmartExplainer. This is the base class that only handles matrices
  of local contributions. The multi-class case is tackled in SmartMultiState.
class_docstr_tok: ["State","pattern","attached","to","SmartExplainer",".","This","is","the","base","class","that","only","handles","matrices","of","local","contributions",".","The","multi-class","case","is","tackled","in","SmartMultiState","."]
docstr: Compute a relative features importance, sum of absolute values
   ​​of the contributions for each
   features importance compute in base 100
  Parameters
  ----------
  contributions: pd.DataFrame
      Matrix containing contributions
  
  Returns
  -------
  pd.Series
      feature importance, One row by feature,
      index of the serie = contributions.columns
docstr_tok: ["Compute","a","relative","features","importance",",","sum","of","absolute","values","\u200b\u200bof","the","contributions","for","each","features","importance","compute","in","base","100","Parameters","--","--","--","--","--","contributions",":","pd.DataFrame","Matrix","containing","contributions","Returns","--","--","--","-","pd.Series","feature","importance",",","One","row","by","feature",",","index","of","the","serie","=","contributions.columns"]
code: def compute_features_import(self, contributions):
      """
      Compute a relative features importance, sum of absolute values
       ​​of the contributions for each
       features importance compute in base 100
      Parameters
      ----------
      contributions: pd.DataFrame
          Matrix containing contributions
  
      Returns
      -------
      pd.Series
          feature importance, One row by feature,
          index of the serie = contributions.columns
      """
      return compute_features_import(contributions)
  
imports: import numpy
  import pandas
  from shapash.decomposition.contributions import inverse_transform_contributions
  from shapash.decomposition.contributions import rank_contributions, assign_contributions
  from shapash.manipulation.filters import hide_contributions
  from shapash.manipulation.filters import cap_contributions
  from shapash.manipulation.filters import sign_contributions
  from shapash.manipulation.filters import cutoff_contributions
  from shapash.manipulation.filters import combine_masks
  from shapash.manipulation.mask import compute_masked_contributions
  from shapash.manipulation.mask import init_mask
  from shapash.manipulation.summarize import summarize, compute_features_import, group_contributions
label_desc: Use image node_id 14 for calling the SmartState obj's underlying member method code with example usage: obj.compute_features_import(contributions) and returns: compute_features_import