[MRG+1] PR for model_evaluation.rst changes to fix issue #3661, "Document negation of loss as scoring parameter"

* doc/modules/model_evaluation.rst in the MattpSoftware fork contains my changes for issue #3661.

* issue-3661/model_evaluation_copy_edited.rst also fixes typos I found when reading the document.

* issue-3661/model_evaluation_edit_notes.txt has the explanation for the changes in model_evaluation_copy_edited.rst, and flags a few other other items for questions.
This is what I show in the HEAD version of model_evaluation.rst

Binary classification
^^^^^^^^^^^^^^^^^^^^^

In a binary classification task, the terms ''positive'' and ''negative''
refer
to the classifier's prediction, and the terms ''true'' and ''false'' refer
to
whether that prediction corresponds to the external judgment (sometimes
known
as the ''observation''). Given these definitions, we can formulate the
following table:

On Wed, Oct 1, 2014 at 4:43 PM, jnothman <notifications@github.com> wrote:

> In doc/modules/model_evaluation.rst:
>
> >
> >  Binary classification
> >  ^^^^^^^^^^^^^^^^^^^^^
> >
> >  In a binary classification task, the terms ''positive'' and ''negative'' refer
> > -to the classifier's prediction and the terms ''true'' and ''false'' refer to
> > +to the classifier's prediction,	and the terms ''true'' and ''false'' refer to
>
> space?
>
> —
> Reply to this email directly or view it on GitHub
> <https://github.com/scikit-learn/scikit-learn/pull/3706/files#r18315599>.
>