Commit 566a6a8d authored by Alain KOMATY's avatar Alain KOMATY

removed unnecessary commands starting with ./bin/

parent 13204f42
Pipeline #8945 canceled with stages
in 9 minutes and 55 seconds
......@@ -32,10 +32,10 @@ Nevertheless, other discrete features, like Local Binary Patterns (LBP) could be
Running the example script
--------------------------
The script ``./bin/boosting_example.py`` is provided to execute digit classification tasks.
The script ``boosting_example.py`` is provided to execute digit classification tasks.
This script has several command line parameters, which vary the behavior of the training and/or testing procedure.
All parameters have a long value (starting with ``--``) and a shortcut (starting with a single ``-``).
These parameters are (see also ``./bin/boosting_example.py --help``):
These parameters are (see also ``boosting_example.py --help``):
To control the type of training, you can select:
......@@ -61,19 +61,19 @@ Four different kinds of experiments can be performed:
1. Uni-variate classification using the stump classifier :py:class:`bob.learn.boosting.StumpMachine`, classifying digits 5 and 6::
$ ./bin/boosting_example.py -vv --trainer-type stump --digits 5 6
$ boosting_example.py -vv --trainer-type stump --digits 5 6
2. Uni-variate classification using the LUT classifier :py:class:`bob.learn.boosting.LUTMachine`, classifying digits 5 and 6::
$ ./bin/boosting_example.py -vv --trainer-type lut --digits 5 6
$ boosting_example.py -vv --trainer-type lut --digits 5 6
3. Multi-variate classification using LUT classifier :py:class:`bob.learn.boosting.LUTMachine` and shared features, classifying all 10 digits::
$ ./bin/boosting_example.py -vv --trainer-type lut --all-digits --multi-variate --feature-selection-style shared
$ boosting_example.py -vv --trainer-type lut --all-digits --multi-variate --feature-selection-style shared
4. Multi-variate classification using LUT classifier :py:class:`bob.learn.boosting.LUTMachine` and independent features, classifying all 10 digits::
$ ./bin/boosting_example.py -vv --trainer-type lut --all-digits --multi-variate --feature-selection-style independent
$ boosting_example.py -vv --trainer-type lut --all-digits --multi-variate --feature-selection-style independent
.. note:
......
......@@ -126,7 +126,6 @@ setup(
# Define the entry points for this package
entry_points={
# Console scripts, which will appear in ./bin/ after buildout
'console_scripts': [
'boosting_example.py = bob.learn.boosting.examples.mnist:main',
],
......
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