[scikit-learn] Help With Text Classification
joel.nothman at gmail.com
Wed Aug 2 22:38:34 EDT 2017
Use a Pipeline to help avoid this kind of issue (and others). You might
also want to do something like
On 3 August 2017 at 12:01, pybokeh <pybokeh at gmail.com> wrote:
> I am studying this example from scikit-learn's site:
> The problem that I need to solve is very similar to this example, except I
> have one
> additional feature column (part #) that is categorical of type string. My
> label or target
> values consist of just 2 values: 0 or 1.
> With that additional feature column, I am transforming it with a
> LabelEncoder and
> then I am encoding it with the OneHotEncoder.
> Then I am concatenating that one-hot encoded column (part #) to the
> feature column (complaint), which I had applied the CountVectorizer and
> TfidfTransformer transformations.
> Then I chose the MultinomialNB model to fit my concatenated training data
> The problem I run into is when I invoke the prediction, I get a dimension
> mis-match error.
> Here's my jupyter notebook gist:
> I would gladly appreciate it if someone can guide me where I went wrong.
> - Daniel
> scikit-learn mailing list
> scikit-learn at python.org
-------------- next part --------------
An HTML attachment was scrubbed...
More information about the scikit-learn