[mlpack] Python examples

Evgeny Freyman evg.freyman at gmail.com
Mon Dec 11 16:17:19 EST 2017


Thank you for the prompt answer

Eugene

On Dec 11, 2017 9:05 PM, "Ryan Curtin" <ryan at ratml.org> wrote:

> On Mon, Dec 11, 2017 at 06:37:10PM +0000, Evgeny Freyman wrote:
> > Hi
> >
> > Cannot find any example of using MLPack from Python. Are they exists?
>
> We haven't generated these yet---hang tight.  Before the 3.0 release
> there needs to be better documentation.
>
> In the mean time you could do the following:
>
> >>> import mlpack
> >>> dir(mlpack)
> ['__builtins__', '__doc__', '__file__', '__name__', '__package__',
> '__path__', 'adaboost', 'approx_kfn', 'arma_numpy', 'cf',
> 'decision_stump', 'decision_tree', 'det', 'emst', 'fastmks',
> 'gmm_generate', 'gmm_probability', 'gmm_train', 'hmm_generate',
> 'hmm_loglik', 'hmm_train', 'hmm_viterbi', 'hoeffding_tree',
> 'kernel_pca', 'kfn', 'kmeans', 'knn', 'krann', 'lars',
> 'linear_regression', 'local_coordinate_coding', 'logistic_regression',
> 'lsh', 'matrix_utils', 'mean_shift', 'nbc', 'nca', 'nmf', 'pca',
> 'perceptron', 'preprocess_binarize', 'preprocess_describe',
> 'preprocess_split', 'radical', 'softmax_regression', 'sparse_coding',
> 'test_python_binding']
>
> That's a list of all the bindings the mlpack package has (plus some
> extras like test_python_binding and arma_numpy).  Then you can use
> help() to get documentation for each.  (This help is generated from the
> same documentation as the --help command for the command-line programs.)
>
> >>> help(mlpack.logistic_regression)
>
> That should give you all you need to actually use the bindings.  For
> matrix data you can pass in your usual numpy or pandas matrices.
>
> These are still somewhat new so speak up if you find any problems!  But
> I think they are bug-free at this point and ready for production use.
>
> --
> Ryan Curtin    | "I know... but I really liked those ones."
> ryan at ratml.org |   - Vincent
>
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