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# BayesNet
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[![License: MIT ](https://img.shields.io/badge/License-MIT-yellow.svg )](https://opensource.org/licenses/MIT)
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Bayesian Network Classifier with libtorch from scratch
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## 0. Setup
Before compiling BayesNet.
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### boost library
[Getting Started ](<https://www.boost.org/doc/libs/1_83_0/more/getting_started/index.html> )
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The best option is install the packages that the Linux distribution have in its repository. If this is the case:
```bash
sudo dnf install boost-devel
```
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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:
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```bash
export BOOST_ROOT=/path/to/library/
```
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In some cases, it is needed to build the library, to do so:
```bash
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.
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### libxlswriter
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```bash
cd lib/libxlsxwriter
make
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make install DESTDIR=/home/rmontanana/Code PREFIX=
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```
Environment variable has to be set:
```bash
export LD_LIBRARY_PATH=/usr/local/lib
```
### Release
```bash
make release
```
### Debug & Tests
```bash
make debug
```
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## 1. Introduction