{ "id": 2479, "title": "Exception when running basic_benchmark.py", "url": "/competitions/predict-closed-questions-on-stack-overflow/discussion/2479", "author_name": "", "post_date": "2012-08-28T14:50:52.697Z", "votes": null, "comment_count": 4, "views": 2446, "content": "

I try to make examples work on my computer but I have a problem when running the basic benchmark

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What can be the cause of this exception? 

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Regards,

\r\n

\r\n

C:\\Users\\A\\Documents\\GitHub\\Stack-Overflow-Competition>C:\\Python32\\python.exe basic_benchmark.py
Reading the data
Extracting features
Training the model
Traceback (most recent call last):
  File "C:\\Python32\\lib\\site-packages\\sklearn\\externals\\joblib\\parallel.py", lin
e 401, in retrieve
    self._output.append(job.get())
  File "C:\\Python32\\lib\\multiprocessing\\pool.py", line 556, in get
    raise self._value
sklearn.externals.joblib.my_exceptions.TransportableException: TransportableExce
ption
___________________________________________________________________________
TypeError                                          Tue Aug 28 16:43:45 2012
PID: 6064                              Python 3.2.3: C:\\Python32\\python.exe
...........................................................................
C:\\Python32\\lib\\site-packages\\sklearn\\ensemble\\forest.py in _parallel_build_tree
s(n_trees=13.5, forest=RandomForestClassifier(bootstrap=True, compute_i...ate ob
ject at 0x04730F40>,
            verbose=2), X=array([[      495.,         4.,         2.,     ...1.,
         3.,        71.,
             4793.]]), y=0     3
1     3
2     3
3     4
4     3
5     3
...   0
140271    3
Name: OpenStatus, Length: 140272, sample_mask=None, X_argsorted=None, seed=83466
4036, verbose=2)
     58                           sample_mask, X_argsorted, seed, verbose):
     59     """Private function used to build a batch of trees within a job."""
     60     random_state = check_random_state(seed)
     61     trees = []
     62
---> 63     for i in range(n_trees):
        i = undefined
        n_trees = 13.5
     64         if verbose > 1:
     65             print(("building tree %d of %d" % (i + 1, n_trees)))
     66         seed = random_state.randint(MAX_INT)
     67

TypeError: 'float' object cannot be interpreted as an integer
___________________________________________________________________________

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "basic_benchmark.py", line 43, in <module>
    main()
  File "basic_benchmark.py", line 27, in main
    rf.fit(fea, data["OpenStatus"])
  File "C:\\Python32\\lib\\site-packages\\sklearn\\ensemble\\forest.py", line 250, in
fit
    for i in range(n_jobs))
  File "C:\\Python32\\lib\\site-packages\\sklearn\\externals\\joblib\\parallel.py", lin
e 475, in __call__
    self.retrieve()
  File "C:\\Python32\\lib\\site-packages\\sklearn\\externals\\joblib\\parallel.py", lin
e 427, in retrieve
    raise exception_type(report)
sklearn.externals.joblib.my_exceptions.JoblibTypeError
", "messages": [ { "id": "13562", "postDate": "08/28/2012 14:50:52", "content": "

I try to make examples work on my computer but I have a problem when running the basic benchmark

\r\n

What can be the cause of this exception? 

\r\n

 

\r\n

Regards,

\r\n

\r\n

C:\\Users\\A\\Documents\\GitHub\\Stack-Overflow-Competition>C:\\Python32\\python.exe basic_benchmark.py
Reading the data
Extracting features
Training the model
Traceback (most recent call last):
  File "C:\\Python32\\lib\\site-packages\\sklearn\\externals\\joblib\\parallel.py", lin
e 401, in retrieve
    self._output.append(job.get())
  File "C:\\Python32\\lib\\multiprocessing\\pool.py", line 556, in get
    raise self._value
sklearn.externals.joblib.my_exceptions.TransportableException: TransportableExce
ption
___________________________________________________________________________
TypeError                                          Tue Aug 28 16:43:45 2012
PID: 6064                              Python 3.2.3: C:\\Python32\\python.exe
...........................................................................
C:\\Python32\\lib\\site-packages\\sklearn\\ensemble\\forest.py in _parallel_build_tree
s(n_trees=13.5, forest=RandomForestClassifier(bootstrap=True, compute_i...ate ob
ject at 0x04730F40>,
            verbose=2), X=array([[      495.,         4.,         2.,     ...1.,
         3.,        71.,
             4793.]]), y=0     3
1     3
2     3
3     4
4     3
5     3
...   0
140271    3
Name: OpenStatus, Length: 140272, sample_mask=None, X_argsorted=None, seed=83466
4036, verbose=2)
     58                           sample_mask, X_argsorted, seed, verbose):
     59     """Private function used to build a batch of trees within a job."""
     60     random_state = check_random_state(seed)
     61     trees = []
     62
---> 63     for i in range(n_trees):
        i = undefined
        n_trees = 13.5
     64         if verbose > 1:
     65             print(("building tree %d of %d" % (i + 1, n_trees)))
     66         seed = random_state.randint(MAX_INT)
     67

TypeError: 'float' object cannot be interpreted as an integer
___________________________________________________________________________

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "basic_benchmark.py", line 43, in <module>
    main()
  File "basic_benchmark.py", line 27, in main
    rf.fit(fea, data["OpenStatus"])
  File "C:\\Python32\\lib\\site-packages\\sklearn\\ensemble\\forest.py", line 250, in
fit
    for i in range(n_jobs))
  File "C:\\Python32\\lib\\site-packages\\sklearn\\externals\\joblib\\parallel.py", lin
e 475, in __call__
    self.retrieve()
  File "C:\\Python32\\lib\\site-packages\\sklearn\\externals\\joblib\\parallel.py", lin
e 427, in retrieve
    raise exception_type(report)
sklearn.externals.joblib.my_exceptions.JoblibTypeError
", "rawMarkdown": "", "votes": null }, { "id": "13563", "postDate": "08/28/2012 15:05:04", "content": "

to rule out problems with parallel jobs, try setting the n_jobs parameter to 1 for\r\nsklearn.ensemble.RandomForestClassifier

", "rawMarkdown": "", "votes": null }, { "id": "13564", "postDate": "08/28/2012 16:07:46", "content": "

Sounds like a bug. Which version of scikit-learn are you using?

", "rawMarkdown": "", "votes": null }, { "id": "13596", "postDate": "08/29/2012 08:49:39", "content": "

I tried setting the n_jobs parameter to 1 for sklearn.ensemble.RandomForestClassifier  but I receive the same error.

\r\n

I am using the scikit-learn-0.11.win32-py3.2.‌exe  from http://www.lfd.uci.edu/~gohlke/pythonlibs/#scikit-learn

\r\n

 

\r\n

 

\r\n

 

\r\n

 

", "rawMarkdown": "", "votes": null }, { "id": "14133", "postDate": "09/09/2012 18:02:18", "content": "

Looking at that stack trace my gut instinct would be that it's caused by using an old verstion of scipy/numpy, I'd try upgrading them and seeing if the error goes away.

", "rawMarkdown": "", "votes": null } ], "comments": [ { "id": 13563, "author_name": "stackunderflow", "author_url": "", "post_date": "08/28/2012 15:05:04", "content": "

to rule out problems with parallel jobs, try setting the n_jobs parameter to 1 for\r\nsklearn.ensemble.RandomForestClassifier

", "votes": null, "replies": [] }, { "id": 13564, "author_name": "", "author_url": "", "post_date": "08/28/2012 16:07:46", "content": "

Sounds like a bug. Which version of scikit-learn are you using?

", "votes": null, "replies": [] }, { "id": 13596, "author_name": "alexandrekowalczyk", "author_url": "", "post_date": "08/29/2012 08:49:39", "content": "

I tried setting the n_jobs parameter to 1 for sklearn.ensemble.RandomForestClassifier  but I receive the same error.

\r\n

I am using the scikit-learn-0.11.win32-py3.2.‌exe  from http://www.lfd.uci.edu/~gohlke/pythonlibs/#scikit-learn

\r\n

 

\r\n

 

\r\n

 

\r\n

 

", "votes": null, "replies": [] }, { "id": 14133, "author_name": "imran2", "author_url": "", "post_date": "09/09/2012 18:02:18", "content": "

Looking at that stack trace my gut instinct would be that it's caused by using an old verstion of scipy/numpy, I'd try upgrading them and seeing if the error goes away.

", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "13562": "", "13563": "", "13564": "", "13596": "", "14133": "" }, "source": "meta" }