Can't get attribute 'Individual'

[szymonk92]

Trying to test example code on Indian Pima Diabetes dataset in Jupyter notebook 5.0.0, Python 3.6, I'm getting an error. Kernel is busy but no processes are running. Turning on debag mode shows:
...
File "c:\users\szymon\anaconda3\envs\tensorflow\lib\multiprocessing\queues.py", line 345, in get return ForkingPickler.loads(res) AttributeError: Can't get attribute 'Individual' on <module 'deap.creator' from 'c:\\users\\szymon\\anaconda3\\envs\\tensorflow\\lib\\site-packages\\deap\\creator.py'> File "c:\users\szymon\anaconda3\envs\tensorflow\lib\multiprocessing\pool.py", line 108, in worker task = get()

[rsteca]

Can you give me the code you are using? It will be easier to debug that way

[szymonk92]

Sure,

### Indian Pima Diabetes  database
names = ['preg', 'plas', 'pres', 'skin', 'test', 'mass', 'pedi', 'age', 'class']
dataframe = pd.read_csv('pima-indians-diabetes.data', names=names)

X, X_test, y, y_test = train_test_split(dataframe.iloc[:,:-1],dataframe.iloc[:,-1], 
                                                    test_size = split, 
                                                    random_state = seed)
X = StandardScaler().fit_transform(X)

kfold = KFold(n_splits=10, random_state=42)

paramgrid = {"kernel": ["rbf"],
             "C"     : np.logspace(-9, 9, num=25, base=10),
             "gamma" : np.logspace(-9, 9, num=25, base=10)}


from evolutionary_search import EvolutionaryAlgorithmSearchCV
cv = EvolutionaryAlgorithmSearchCV(estimator=SVC(),
                                   params=paramgrid,
                                   scoring="accuracy",
                                   cv=kfold,
                                   verbose=1,
                                   population_size=50,
                                   gene_mutation_prob=0.10,
                                   gene_crossover_prob=0.5,
                                   tournament_size=3,
                                   generations_number=5,
                                   n_jobs=4)
%time cv.fit(X, y)

cv.best_score_, cv.best_params_

[rsteca]

I couldn't reproduce the error. Can you tell me which version of the library are you using? also, which version of deap have you installed? I have never tested it using anaconda, can you try it using pip to see if you still have the problem?

[szymonk92]

I have no idea how to check sklearn-deap version, but here are some details:

Requirement already satisfied: sklearn-deap in c:\users\szymon\anaconda3\envs\tensorflow\lib\site-packages
Requirement already satisfied: numpy>=1.9.3 in c:\users\szymon\anaconda3\envs\tensorflow\lib\site-packages (from sklearn-deap)
Requirement already satisfied: deap>=1.0.2 in c:\users\szymon\anaconda3\envs\tensorflow\lib\site-packages (from sklearn-deap)
Requirement already satisfied: scikit-learn>=0.18.0 in c:\users\szymon\anaconda3\envs\tensorflow\lib\site-packages (from sklearn-deap)
Requirement already satisfied: scipy>=0.16.0 in c:\users\szymon\anaconda3\envs\tensorflow\lib\site-packages (from sklearn-deap)

I have installed this library using pip on anaconda environment.

Starting search it shows me

Types [1, 2, 2] and maxint [0, 24, 24] detected
--- Evolve in 625 possible combinations ---

and then calculating forever

[sundisktop]

I had same problem. Seems like it in n_jobs parameter on Windows system. On Linux all works fine

[rsteca]

This should be fixed on version 0.2.2

[sparo-jack]

still have the problem
Traceback (most recent call last):
File "C:\Users\uesr\Anaconda3\lib\multiprocessing\process.py", line 258, in _bootstrap
self.run()
File "C:\Users\uesr\Anaconda3\lib\multiprocessing\process.py", line 93, in run
self._target(*self._args, **self._kwargs)
File "C:\Users\uesr\Anaconda3\lib\multiprocessing\pool.py", line 108, in worker
task = get()
File "C:\Users\uesr\Anaconda3\lib\multiprocessing\queues.py", line 337, in get
return _ForkingPickler.loads(res)
AttributeError: Can't get attribute 'Individual' on <module 'deap.creator' from 'C:\Users\uesr\Anaconda3\lib\site-packages\deap\creator.py'>

package version:
deap-1.2.2
sklearn-deap-0.2.2