On 12 August 2012 15:35, Zach Bastick <[email protected]> wrote:
> I have tried various machine learning algorithms from scikit learn but
> can't find a good prediction model.
> The features I'm using are the tf-idf of set of text documents,
> correlated with human ratings assigned to each document. I'm thinking
> that I must be doing something wrong as the scores can't be that bad
> (not to mention negative?)
>
> If someone could have a look at it, I'd really appreciate it. I didn't
> upload to a github gist because they won't let me upload the dataset
> directory. So I've uploaded my really short code (regression.py) AND the
> original data set (/texts) here (625K):
> https://dl.dropbox.com/u/74279156/regression.zip
>
> This is my output:
> C:\python code\program>python regression.py
> loading texts...
> n_samples: 53, n_features: 6284
>
> LinearRegresson
> [ 0.34662496 0.23446674 0.30332109 0.3163838 0.01607913]
> Accuracy: 0.24 (+/- 0.06)
>
> SVR linear
> [-0.05521329 -1.61280714 -0.67428098 -0.8805647 -2.20730703]
> Accuracy: -1.09 (+/- 0.37)
>
> SVR poly 4 degrees
> [-0.18814233 -1.78480475 -0.88158686 -1.05944432 -2.40284073]
> Accuracy: -1.26 (+/- 0.38)
>
> SVR sigmoid
> [-0.18814233 -1.78480475 -0.88158686 -1.05944432 -2.40284073]
> Accuracy: -1.26 (+/- 0.38)
>
>
> Please tell me what's wrong.. I'm dying to know how to get scikit-lean
> to predict based on this dataset.
>
> Thanks
>
> Zach
>
>
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Where can I get the plugins from?
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threat landscape has changed and how IT managers can respond. Discussions
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threats. http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/
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