class_docstr: Igel is the base model to use the fit, evaluate and predict functions of the sklearn library
class_docstr_tok: ["Igel","is","the","base","model","to","use","the","fit",",","evaluate","and","predict","functions","of","the","sklearn","library"]
docstr: evaluate a pre-fitted model and save results to a evaluation.json
  @return: None
docstr_tok: ["evaluate","a","pre-fitted","model","and","save","results","to","a","evaluation.json","@","return",":","None"]
code: def evaluate(self, **kwargs):
      """
      evaluate a pre-fitted model and save results to a evaluation.json
      @return: None
      """
      x_val = None
      y_true = None
      eval_results = None
  
      try:
          model = self._load_model()
          if self.model_type != "clustering":
              x_val, y_true = self._prepare_eval_data()
              y_pred = model.predict(x_val)
              eval_results = self.get_evaluation(
                  model=model,
                  x_test=x_val,
                  y_true=y_true,
                  y_pred=y_pred,
                  **kwargs,
              )
          else:
              x_val = self._prepare_clustering_data()
              y_pred = model.predict(x_val)
              eval_results = model.score(x_val, y_pred)
  
          logger.info(
              f"saving fit description to {self.evaluation_file}"
          )
          with open(self.evaluation_file, "w", encoding="utf-8") as f:
              json.dump(eval_results, f, ensure_ascii=False, indent=4)
  
      except Exception as e:
          logger.exception(f"error occured during evaluation: {e}")
  
imports: import json
  import logging
  import os
  import warnings
  import joblib
  import numpy
  import pandas
  from sklearn.model_selection import cross_validate, train_test_split
  from sklearn.multioutput import MultiOutputClassifier, MultiOutputRegressor
  from skl2onnx import convert_sklearn
  from skl2onnx.common.data_types import FloatTensorType
label_desc: Use image node_id 12 for calling the Igel obj's underlying member method code with example usage: obj.evaluate() without return types