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1

I keep getting the following error when I try to run some clustering algorithms:

sklearn.externals.joblib.externals.loky.process_executor.BrokenProcessPool: A task has failed to un-serialize. Please ensure that the arguments of the function are all picklable.

I tried the following:

• Updating scikit-learn to 0.20.2



• 
  

  Changing n_jobs = 1 and -1

  
  
  

  grid = 'km__n_clusters': self._clusters, 'NN__alpha': self._nn_reg, 'NN__hidden_layer_sizes': self._nn_arch
  mlp = MLPClassifier(activation='relu', max_iter=2000, early_stopping=True, random_state=self._details.seed)
  km = kmeans(random_state=self._details.seed, n_jobs=self._details.threads) #tried n_jobs=self._details.threads
  pipe = Pipeline([('km', km), ('NN', mlp)], memory=experiments.pipeline_memory)
  gs, _ = self.gs_with_best_estimator(pipe, grid, type='kmeans')
  self.log("KMmeans Grid search complete")
  

  
  

python scikit-learn

share|improve this question

edited Mar 24 at 11:44

desertnaut

22k84884

asked Mar 24 at 2:43

AbduAbdu

61

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Where exactly does the error pop up?? Please post the complete error trace (text, no images).
  
  – desertnaut
  Mar 24 at 11:46
  

  
  
  
  

add a comment | 

1

I keep getting the following error when I try to run some clustering algorithms:

sklearn.externals.joblib.externals.loky.process_executor.BrokenProcessPool: A task has failed to un-serialize. Please ensure that the arguments of the function are all picklable.

I tried the following:

• Updating scikit-learn to 0.20.2



• 
  

  Changing n_jobs = 1 and -1

  
  
  

  grid = 'km__n_clusters': self._clusters, 'NN__alpha': self._nn_reg, 'NN__hidden_layer_sizes': self._nn_arch
  mlp = MLPClassifier(activation='relu', max_iter=2000, early_stopping=True, random_state=self._details.seed)
  km = kmeans(random_state=self._details.seed, n_jobs=self._details.threads) #tried n_jobs=self._details.threads
  pipe = Pipeline([('km', km), ('NN', mlp)], memory=experiments.pipeline_memory)
  gs, _ = self.gs_with_best_estimator(pipe, grid, type='kmeans')
  self.log("KMmeans Grid search complete")
  

  
  

python scikit-learn

share|improve this question

edited Mar 24 at 11:44

desertnaut

22k84884

asked Mar 24 at 2:43

AbduAbdu

61

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Where exactly does the error pop up?? Please post the complete error trace (text, no images).
  
  – desertnaut
  Mar 24 at 11:46
  

  
  
  
  

add a comment | 

I keep getting the following error when I try to run some clustering algorithms:

sklearn.externals.joblib.externals.loky.process_executor.BrokenProcessPool: A task has failed to un-serialize. Please ensure that the arguments of the function are all picklable.

I tried the following:

• Updating scikit-learn to 0.20.2



• 
  

  Changing n_jobs = 1 and -1

  
  
  

  grid = 'km__n_clusters': self._clusters, 'NN__alpha': self._nn_reg, 'NN__hidden_layer_sizes': self._nn_arch
  mlp = MLPClassifier(activation='relu', max_iter=2000, early_stopping=True, random_state=self._details.seed)
  km = kmeans(random_state=self._details.seed, n_jobs=self._details.threads) #tried n_jobs=self._details.threads
  pipe = Pipeline([('km', km), ('NN', mlp)], memory=experiments.pipeline_memory)
  gs, _ = self.gs_with_best_estimator(pipe, grid, type='kmeans')
  self.log("KMmeans Grid search complete")
  

  
  

python scikit-learn

share|improve this question

edited Mar 24 at 11:44

desertnaut

22k84884

asked Mar 24 at 2:43

AbduAbdu

61

share|improve this question

edited Mar 24 at 11:44

desertnaut

22k84884

asked Mar 24 at 2:43

AbduAbdu

61

share|improve this question

edited Mar 24 at 11:44

desertnaut

22k84884

asked Mar 24 at 2:43

AbduAbdu

61

edited Mar 24 at 11:44

desertnaut

22k84884

edited Mar 24 at 11:44

desertnaut

22k84884

asked Mar 24 at 2:43

AbduAbdu

61

asked Mar 24 at 2:43

AbduAbdu

61