BayesNet

Bayesian Network Classifier with libtorch from scratch

0. Setup

Before compiling BayesNet.

Miniconda

To be able to run Python Classifiers such as STree, ODTE, SVC, etc. it is needed to install Miniconda. To do so, download the installer from Miniconda and run it. It is recommended to install it in the home folder.

In Linux sometimes the library libstdc++ is mistaken from the miniconda installation and produces the next message when running the b_xxxx executables:

libstdc++.so.6: version `GLIBCXX_3.4.32' not found (required by b_xxxx)

The solution is to erase the libstdc++ library from the miniconda installation:

MPI

In Linux just install openmpi & openmpi-devel packages. Only if cmake can't find openmpi installation (like in Oracle Linux) set the following variable:

export MPI_HOME="/usr/lib64/openmpi"

In Mac OS X, install mpich with brew and if cmake doesn't find it, edit mpicxx wrapper to remove the ",-commons,use_dylibs" from final_ldflags

vi /opt/homebrew/bin/mpicx

boost library

Getting Started

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

1. Introduction