Sorry about that, the RTF reader is from the Pyth library:
http://pypi.python.org/pypi/pyth/

I think that's all that's needed.

Thanks for taking a look!

Zach


On 11/08/2012 22:55, Robert Layton wrote:
On 12 August 2012 15:35, Zach Bastick <[email protected] <mailto:[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?
--

Public key at: http://pgp.mit.edu/ Search for this email address and select the key from "2011-08-19" (key id: 54BA8735)



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