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<!--
If your issue is a usage question, submit it here instead:
- The imbalanced learn gitter: https://gitter.im/scikit-learn-contrib/imbalanced-learn
-->
<!-- Instructions For Filing a Bug: https://github.com/scikit-learn-contrib/imbalanced-learn/blob/master/CONTRIBUTING.md#filing-bugs -->
#### Description
<!-- Example: Joblib Error thrown when calling fit on LatentDirichletAllocation with evaluate_every > 0-->
#### Steps/Code to Reproduce
<!--
Example:
```
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.decomposition import LatentDirichletAllocation
docs = ["Help I have a bug" for i in range(1000)]
vectorizer = CountVectorizer(input=docs, analyzer='word')
lda_features = vectorizer.fit_transform(docs)
lda_model = LatentDirichletAllocation(
n_topics=10,
learning_method='online',
evaluate_every=10,
n_jobs=4,
)
model = lda_model.fit(lda_features)
```
If the code is too long, feel free to put it in a public gist and link
it in the issue: https://gist.github.com
-->
#### Expected Results
<!-- Example: No error is thrown. Please paste or describe the expected results.-->
#### Actual Results
<!-- Please paste or specifically describe the actual output or traceback. -->
#### Versions
<!--
Please run the following snippet and paste the output below.
import platform; print(platform.platform())
import sys; print("Python", sys.version)
import numpy; print("NumPy", numpy.__version__)
import scipy; print("SciPy", scipy.__version__)
import sklearn; print("Scikit-Learn", sklearn.__version__)
import imblearn; print("Imbalanced-Learn", imblearn.__version__)
-->
<!-- Thanks for contributing! -->
|
