Bayesian Network Classifiers using libtorch from scratch
| .vscode | ||
| cmake/modules | ||
| config | ||
| data | ||
| diagrams | ||
| lib | ||
| sample | ||
| src | ||
| tests | ||
| .clang-tidy | ||
| .clang-uml | ||
| .gitignore | ||
| .gitmodules | ||
| CMakeLists.txt | ||
| gcovr.cfg | ||
| grid_stree.json | ||
| LICENSE | ||
| Makefile | ||
| README.md | ||
| stree_results.json | ||
BayesNet
Bayesian Network Classifier with libtorch from scratch
0. Setup
Before compiling BayesNet.
boost library
The best option is install the packages that the Linux distribution have in its repository. If this is the case:
sudo dnf install boost-devel
If this is not possible and the compressed packaged is installed, the following environment variable has to be set pointing to the folder where it was unzipped to:
export BOOST_ROOT=/path/to/library/
In some cases, it is needed to build the library, to do so:
cd /path/to/library
mkdir own
./bootstrap.sh --prefix=/path/to/library/own
./b2 install
export BOOST_ROOT=/path/to/library/own/
Don't forget to add the export BOOST_ROOT statement to .bashrc or wherever it is meant to be.
libxlswriter
cd lib/libxlsxwriter
make
make install DESTDIR=/home/rmontanana/Code PREFIX=
Environment variable has to be set:
export LD_LIBRARY_PATH=/usr/local/lib
Release
make release
Debug & Tests
make debug