More robust DMatrix creation from a sparse matrix

[khotilov]

Addresses #1583

The new "explicit" XGDMatrixCreateFromCS*Ex functions are pretty much duplicates of the old ones with an extra argument, slight code change, and slightly safer types. The old ones are marked as \deprecated in their doc.

I've updated the Python interface, but need to think a bit more about R (would like to make it handle the 64 bit indexing properly). And I didn't touch jvm.

[tqchen]

https://travis-ci.org/dmlc/xgboost/builds/162198885 see the lint and lightweight test error. Note that lightweight test comes without sklearn or other external dependencies

[tqchen]

still another lint problem in c_api.cc final step to go!

[khotilov]

I guess I just have to install python2 to make the linter work locally for me.

[CodingCat]

I will push jvm changes after this is merged

[khotilov]

I've just updated the R-package to just use the new interface. The long vector support would need to be another issue.

[tqchen]

Thanks, some final comments

• Redirect the old functions to the new function, so implementation won't be duplicated
• Fix the indentation in the function parameters

[khotilov]

Is that better?
There are various function parameter indentations in the current code though.

[tqchen]

Thanks! this is merged

[chleibig]

Thank you very much for this PR! I am using the python bindings and noticed that creating a DMatrix from
sparse matrices works correctly due to this PR. If the DMatrix is however created from a sparse matrix file (tested libsvm txt format, which is supported according to the API docs), the num_col are not correctly set if the last feature column is zero, even though the feature_names are provided and could be used to set this correctly. In particular, it seems that the XGDMatrixCreateFromFile function needs an update similar to the changes introduced here for the XGDMatrixCreateFromCS*Ex functions.