class_docstr: Encapsulates results from an estimator on a testing set to provide a
  simplified API from other modules. All parameters are optional, just
  fill the ones you need for your analysis.
  
  Parameters
  ----------
  estimator : sklearn estimator
      Must have a ``feature_importances_`` attribute.
  y_true : array-like
      Target predicted classes (estimator predictions).
  y_pred : array-like
      Correct target values (ground truth).
  y_score : array-like
      Target scores (estimator predictions).
  feature_names : array-like
      Feature names.
  target_names : list
      List containing the names of the target classes
  estimator_name : str
      Identifier for the model. This can be later used to identify the
      estimator when generating reports.
class_docstr_tok: ["Encapsulates","results","from","an","estimator","on","a","testing","set","to","provide","a","simplified","API","from","other","modules",".","All","parameters","are","optional",",","just","fill","the","ones","you","need","for","your","analysis",".","Parameters","--","--","--","--","--","estimator",":","sklearn","estimator","Must","have","a","``","feature_importances_","``","attribute",".","y_true",":","array-like","Target","predicted","classes","(","estimator","predictions",")",".","y_pred",":","array-like","Correct","target","values","(","ground","truth",")",".","y_score",":","array-like","Target","scores","(","estimator","predictions",")",".","feature_names",":","array-like","Feature","names",".","target_names",":","list","List","containing","the","names","of","the","target","classes","estimator_name",":","str","Identifier","for","the","model",".","This","can","be","later","used","to","identify","the","estimator","when","generating","reports","."]
docstr: Make HTML report
  
  Parameters
  ----------
  template: str, or pathlib.Path, optional
      HTML or Markdown template with jinja2 format. If a pathlib.Path
      object is passed, the content of the file is read. Within the
      template, the evaluator is passed as "e", so you can use things
      like {{e.confusion_matrix()}} or any other attribute/method. If
      None, a default template is used
  
  style: str
      Path to a css file to apply style to the report. If None, no
      style will be applied
  
  Returns
  -------
  Report
      Returns the contents of the report if path is None.
docstr_tok: ["Make","HTML","report","Parameters","--","--","--","--","--","template",":","str",",","or","pathlib.Path",",","optional","HTML","or","Markdown","template","with","jinja2","format",".","If","a","pathlib.Path","object","is","passed",",","the","content","of","the","file","is","read",".","Within","the","template",",","the","evaluator","is","passed","as","``","e","''",",","so","you","can","use","things","like","{","{","e.confusion_matrix","(",")","}","}","or","any","other","attribute\/method",".","If","None",",","a","default","template","is","used","style",":","str","Path","to","a","css","file","to","apply","style","to","the","report",".","If","None",",","no","style","will","be","applied","Returns","--","--","--","-","Report","Returns","the","contents","of","the","report","if","path","is","None","."]
code: def make_report(self, template=None):
      """
      Make HTML report
  
      Parameters
      ----------
      template: str, or pathlib.Path, optional
          HTML or Markdown template with jinja2 format. If a pathlib.Path
          object is passed, the content of the file is read. Within the
          template, the evaluator is passed as "e", so you can use things
          like {{e.confusion_matrix()}} or any other attribute/method. If
          None, a default template is used
  
      style: str
          Path to a css file to apply style to the report. If None, no
          style will be applied
  
      Returns
      -------
      Report
          Returns the contents of the report if path is None.
  
      """
      return Report(self.html_serializable(), template)
  
imports: import matplotlib.pyplot
  from sklearn_evaluation.plot.util import requires_properties
  from sklearn_evaluation.report.serialize import EvaluatorHTMLSerializer
  from sklearn_evaluation.report.report import Report
  from .util import estimator_type, class_name
  from .None import plot
  from .telemetry import SKLearnEvaluationLogger
label_desc: Use image node_id 19 for calling the ClassifierEvaluator obj's underlying member method code with example usage: obj.make_report(template) and returns: Report