DOC Explicitly use https in index.rst links
@@ -252,7 +252,7 @@ features::
.. topic:: Related links:
- _`Public datasets in svmlight / libsvm format`: http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/
+ _`Public datasets in svmlight / libsvm format`: https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets
_`Faster API-compatible implementation`: https://github.com/mblondel/svmlight-loader
@@ -268,15 +268,15 @@ DataFrame are also acceptable.
Here are some recommended ways to load standard columnar data into a
format usable by scikit-learn:
-* `pandas.io <http://pandas.pydata.org/pandas-docs/stable/io.html>`_
+* `pandas.io <https://pandas.pydata.org/pandas-docs/stable/io.html>`_
provides tools to read data from common formats including CSV, Excel, JSON
and SQL. DataFrames may also be constructed from lists of tuples or dicts.
Pandas handles heterogeneous data smoothly and provides tools for
manipulation and conversion into a numeric array suitable for scikit-learn.
-* `scipy.io <http://docs.scipy.org/doc/scipy/reference/io.html>`_
+* `scipy.io <https://docs.scipy.org/doc/scipy/reference/io.html>`_
specializes in binary formats often used in scientific computing
context such as .mat and .arff
-* `numpy/routines.io <http://docs.scipy.org/doc/numpy/reference/routines.io.html>`_
+* `numpy/routines.io <https://docs.scipy.org/doc/numpy/reference/routines.io.html>`_
for standard loading of columnar data into numpy arrays
* scikit-learn's :func:`datasets.load_svmlight_file` for the svmlight or libSVM
sparse format
@@ -288,14 +288,14 @@ For some miscellaneous data such as images, videos, and audio, you may wish to
refer to:
* `skimage.io <http://scikit-image.org/docs/dev/api/skimage.io.html>`_ or
- `Imageio <http://imageio.readthedocs.io/en/latest/userapi.html>`_
+ `Imageio <https://imageio.readthedocs.io/en/latest/userapi.html>`_
for loading images and videos to numpy arrays
-* `scipy.misc.imread <http://docs.scipy.org/doc/scipy/reference/generated/scipy.
+* `scipy.misc.imread <https://docs.scipy.org/doc/scipy/reference/generated/scipy.
misc.imread.html#scipy.misc.imread>`_ (requires the `Pillow
<https://pypi.python.org/pypi/Pillow>`_ package) to load pixel intensities
data from various image file formats
* `scipy.io.wavfile.read
- <http://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.io.wavfile.read.html>`_
+ <https://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.io.wavfile.read.html>`_
for reading WAV files into a numpy array
Categorical (or nominal) features stored as strings (common in pandas DataFrames)
