scrub outdated benchmarks from README

README.rst

@@ -70,31 +70,6 @@ and here are some of the highlights.
    easy to modify and introduce additional noise models and regularizers
    in the future.
 
-Benchmarks
-~~~~~~~~~~
-
-Here is table comparing ``pyglmnet`` against ``scikit-learn``'s
-``linear_model``, ``statsmodels``, and ``R``.
-
-The numbers below are run time (in milliseconds) to fit a :math:`1000`
-samples x :math:`100` predictors sparse matrix (density :math:`0.05`).
-This was done on a c. 2011 Macbook Pro, so your numbers may vary.
-
-+------------+------------+----------------+---------------+---------+
-| distr      | pyglmnet   | scikit-learn   | statsmodels   | R       |
-+============+============+================+===============+=========+
-| gaussian   | 6.8        | 1.2            | 29.8          | 10.3    |
-+------------+------------+----------------+---------------+---------+
-| binomial   | 16.3       | 4.5            | 89.3          | --      |
-+------------+------------+----------------+---------------+---------+
-| poisson    | 5.8        | --             | 117.2         | 156.1   |
-+------------+------------+----------------+---------------+---------+
-
-We provide a function called ``BenchMarkGLM()`` in ``pyglmnet.datasets``
-if you would like to run these benchmarks yourself, but you need to take
-care of the dependencies: ``scikit-learn``, ``Rpy2``, and
-``statsmodels`` yourself.
-
 Installation
 ~~~~~~~~~~~~
 
@@ -201,4 +176,4 @@ MIT License Copyright (c) 2016-2019 Pavan Ramkumar
 .. |DOI| image:: https://zenodo.org/badge/55302570.svg
    :target: https://zenodo.org/badge/latestdoi/55302570
 .. _[Documentation (stable version)]: http://glm-tools.github.io/pyglmnet
-.. _[Documentation (development version)]: https://circleci.com/api/v1.1/project/github/glm-tools/pyglmnet/latest/artifacts/0/html/index.html?branch=master
+.. _[Documentation (development version)]: https://circleci.com/api/v1.1/project/github/glm-tools/pyglmnet/latest/artifacts/0/html/index.html?branch=master