<!-- If your issue is a usage question, submit it here instead: - StackOverflow with the scikit-learn tag: https://stackoverflow.com/questions/tagged/scikit-learn - Mailing List: https://mail.python.org/mailman/listinfo/scikit-learn For more information, see User Questions: http://scikit-learn.org/stable/support.html#user-questions --> <!-- Instructions For Filing a Bug: https://github.com/scikit-learn/scikit-learn/blob/master/CONTRIBUTING.md#filing-bugs --> #### Description <!-- Example: Joblib Error thrown when calling fit on LatentDirichletAllocation with evaluate_every > 0--> This demo provides an example of how to tune a Random Forest classifier using GridSearchCV on the MNIST dataset. #### Steps/Code to Reproduce link to code: https://github.com/NeuroDataDesign/team-forbidden-forest <!-- Example: ```python 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 --> <!-- Thanks for contributing! -->
Description
This demo provides an example of how to tune a Random Forest classifier using GridSearchCV on the MNIST dataset.
Steps/Code to Reproduce
link to code: https://github.com/NeuroDataDesign/team-forbidden-forest