On 09/22/2014 11:36 AM, Lars Buitinck wrote:
> 2014-09-22 11:32 GMT+02:00 Andy :
>> PyStruct uses
>> minimum_spanning_tree
> I removed that a few weeks ago, because nothing in scikit-learn was
> using it. You can get it from scipy.sparse.csgraph.
Thanks.
I think when I wrote that it was pretty fres
2014-09-22 11:32 GMT+02:00 Andy :
> PyStruct uses
> minimum_spanning_tree
I removed that a few weeks ago, because nothing in scikit-learn was
using it. You can get it from scipy.sparse.csgraph.
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PyStruct uses
minimum_spanning_tree
check_random_state
gen_even_slices
shuffle
check_arrays (this one is just for a backport of train_test_split, which
I probably don't need any more)
Cheers,
Andy
On 09/15/2014 03:40 PM, Mathieu Blondel wrote:
lightning is using the following utils:
- check
2014-09-15 15:40 GMT+02:00 Mathieu Blondel :
> lightning is using the following utils:
>
> - check_random_state
> - safe_sparse_dot
> - shuffle
> - safe_mask
> - sklearn.utils.testing.*
seqlearn is using
* atleast2d_or_csr
* check_random_state
* logsumexp
* safe_sparse_dot
so it's broken no
Andy,
Indeed, this will mostly depend on the number of public utils we have.
However, using submodules can help structure our public utils.
M.
On Wed, Sep 17, 2014 at 6:32 PM, Andy wrote:
> On 09/15/2014 03:40 PM, Mathieu Blondel wrote:
>
>> lightning is using the following utils:
>>
>> - chec
On 09/15/2014 03:40 PM, Mathieu Blondel wrote:
> lightning is using the following utils:
>
> - check_random_state
> - safe_sparse_dot
> - shuffle
> - safe_mask
> - sklearn.utils.testing.*
>
> The latter is not big deal but I like importing assertions from the
> same place.
>
> On a second thought,
I would add to this lists:
- check_array;
- check_consistent_length;
- check_X_y.
Those are very useful.
Arnaud
On 15 Sep 2014, at 20:03, Olivier Grisel wrote:
> 2014-09-15 6:40 GMT-07:00 Mathieu Blondel :
>> lightning is using the following utils:
>>
>> - check_random_st
2014-09-15 6:40 GMT-07:00 Mathieu Blondel :
> lightning is using the following utils:
>
> - check_random_state
> - safe_sparse_dot
> - shuffle
> - safe_mask
> - sklearn.utils.testing.*
>
> The latter is not big deal but I like importing assertions from the same
> place.
>
> On a second thought, imp
lightning is using the following utils:
- check_random_state
- safe_sparse_dot
- shuffle
- safe_mask
- sklearn.utils.testing.*
The latter is not big deal but I like importing assertions from the same
place.
On a second thought, importing all public utils in __init__.py might
quickly become messy
We should survey what other packages use. I'll have a look at what
lightning uses later.
Mathieu
On Sat, Sep 13, 2014 at 2:23 AM, Andy wrote:
> +1 of cleaning up __init__.py (maybe no implementations at all?)
> +1 for making private methods start with underscore (which will break
> everything
+1 of cleaning up __init__.py (maybe no implementations at all?)
+1 for making private methods start with underscore (which will break
everything ^^)
Also we need to add utils to the References then.
No idea how to decide what should be public and what not, though.
On 09/08/2014 04:01 PM, Mat
I'm happy with these proposals, but expect that some users will find
themselves using sparsefuncs or extmath.
On 9 September 2014 07:31, Kyle Kastner wrote:
> I agree as well. Maybe default to everything other than validation
> private? Then see what people want to become public? Don't know wha
I agree as well. Maybe default to everything other than validation
private? Then see what people want to become public? Don't know what
nilearn is using but that should obviously be public too...
On Mon, Sep 8, 2014 at 5:17 PM, Olivier Grisel wrote:
> +1 as well for the combined proposal of Gael
+1 as well for the combined proposal of Gael and Matthieu (explicit
__all__ in sklearn/util/__init__.py) + prefixing private utils with
`_`.
--
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I agree with everything you said, Matthieu (which of course does not
answer the questions that you raise).
Gaël
On Mon, Sep 08, 2014 at 11:01:44PM +0900, Mathieu Blondel wrote:
> Maintaining backward compatibility for a subset of the utils only means that
> from now on we will have to decide whet
Maintaining backward compatibility for a subset of the utils only means
that from now on we will have to decide whether an util deserves to be
public or not. While we are at it, I would rather make it explicit and use
an underscore prefix for private utils and no prefix for public utils.
This can b
Hi people,
So far we have had no policy of backward compatibility in sklearn/utils.
However, some of the utilities there are very useful for packages that
want to extend scikit-learn's functionality, such as seqlearn,
sklearn-theano, nilearn...
The latest set of changes in the validation utilitie
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