forked from moreo/QuaPy
56 lines
1.9 KiB
ReStructuredText
56 lines
1.9 KiB
ReStructuredText
Installation
|
|
------------
|
|
|
|
QuaPy can be easily installed via `pip`
|
|
|
|
::
|
|
|
|
pip install quapy
|
|
|
|
See `pip page <https://pypi.org/project/QuaPy/>`_ for older versions.
|
|
|
|
Requirements
|
|
************
|
|
|
|
* scikit-learn, numpy, scipy
|
|
* pytorch (for QuaNet)
|
|
* svmperf patched for quantification (see below)
|
|
* joblib
|
|
* tqdm
|
|
* pandas, xlrd
|
|
* matplotlib
|
|
|
|
|
|
SVM-perf with quantification-oriented losses
|
|
********************************************
|
|
|
|
In order to run experiments involving SVM(Q), SVM(KLD), SVM(NKLD),
|
|
SVM(AE), or SVM(RAE), you have to first download the
|
|
`svmperf <http://www.cs.cornell.edu/people/tj/svm_light/svm_perf.html>`_
|
|
package, apply the patch
|
|
`svm-perf-quantification-ext.patch <https://github.com/HLT-ISTI/QuaPy/blob/master/svm-perf-quantification-ext.patch>`_,
|
|
and compile the sources.
|
|
The script
|
|
`prepare_svmperf.sh <https://github.com/HLT-ISTI/QuaPy/blob/master/prepare_svmperf.sh>`_,
|
|
does all the job. Simply run:
|
|
|
|
::
|
|
|
|
./prepare_svmperf.sh
|
|
|
|
|
|
The resulting directory `./svm_perf_quantification` contains the
|
|
patched version of `svmperf` with quantification-oriented losses.
|
|
|
|
The
|
|
`svm-perf-quantification-ext.patch <https://github.com/HLT-ISTI/QuaPy/blob/master/svm-perf-quantification-ext.patch>`_
|
|
is an extension of the patch made available by
|
|
`Esuli et al. 2015 <https://dl.acm.org/doi/abs/10.1145/2700406?casa_token=8D2fHsGCVn0AAAAA:ZfThYOvrzWxMGfZYlQW_y8Cagg-o_l6X_PcF09mdETQ4Tu7jK98mxFbGSXp9ZSO14JkUIYuDGFG0>`_
|
|
that allows SVMperf to optimize for
|
|
the `Q` measure as proposed by
|
|
`Barranquero et al. 2015 <https://www.sciencedirect.com/science/article/abs/pii/S003132031400291X>`_
|
|
and for the `KLD` and `NKLD` as proposed by
|
|
`Esuli et al. 2015 <https://dl.acm.org/doi/abs/10.1145/2700406?casa_token=8D2fHsGCVn0AAAAA:ZfThYOvrzWxMGfZYlQW_y8Cagg-o_l6X_PcF09mdETQ4Tu7jK98mxFbGSXp9ZSO14JkUIYuDGFG0>`_
|
|
for quantification.
|
|
This patch extends the former by also allowing SVMperf to optimize for
|
|
`AE` and `RAE`. |