" lang="en-US">
<head>
<script type="text/javascript" src="jquery.js"></script>
<script type="text/javascript" src="dynsections.js"></script>
<script type="text/javascript" src="clipboard.js"></script>
<script type="text/javascript" src="navtreedata.js"></script>
<script type="text/javascript" src="navtree.js"></script>
<script type="text/javascript" src="resize.js"></script>
<script type="text/javascript" src="cookie.js"></script>
<script type="text/javascript" src="search/searchdata.js"></script>
<script type="text/javascript" src="search/search.js"></script>
</head>
 |
BayesNet 1.0.5
Bayesian Network Classifiers using libtorch from scratch
|
<script type="text/javascript">
/* @license magnet:?xt=urn:btih:d3d9a9a6595521f9666a5e94cc830dab83b65699&dn=expat.txt MIT */
var searchBox = new SearchBox("searchBox", "search/",'.html');
/* @license-end */
</script>
<script type="text/javascript">
/* @license magnet:?xt=urn:btih:d3d9a9a6595521f9666a5e94cc830dab83b65699&dn=expat.txt MIT */
$(function() { codefold.init(0); });
/* @license-end */
</script>
<script type="text/javascript" src="menudata.js"></script>
<script type="text/javascript" src="menu.js"></script>
<script type="text/javascript">
/* @license magnet:?xt=urn:btih:d3d9a9a6595521f9666a5e94cc830dab83b65699&dn=expat.txt MIT */
$(function() {
initMenu('',true,false,'search.php','Search',true);
$(function() { init_search(); });
});
/* @license-end */
</script>
<script type="text/javascript">
/* @license magnet:?xt=urn:btih:d3d9a9a6595521f9666a5e94cc830dab83b65699&dn=expat.txt MIT */
$(function(){initNavTree('classbayesnet_1_1_network.html',''); initResizable(true); });
/* @license-end */
</script>
Loading...
Searching...
No Matches
Public Member Functions |
| Network (float) |
|
| Network (const Network &) |
|
torch::Tensor & | getSamples () |
|
float | getMaxThreads () const |
|
void | addNode (const std::string &) |
|
void | addEdge (const std::string &, const std::string &) |
|
std::map< std::string, std::unique_ptr< Node > > & | getNodes () |
|
std::vector< std::string > | getFeatures () const |
|
int | getStates () const |
|
std::vector< std::pair< std::string, std::string > > | getEdges () const |
|
int | getNumEdges () const |
|
int | getClassNumStates () const |
|
std::string | getClassName () const |
|
void | fit (const std::vector< std::vector< int > > &input_data, const std::vector< int > &labels, const std::vector< double > &weights, const std::vector< std::string > &featureNames, const std::string &className, const std::map< std::string, std::vector< int > > &states) |
|
void | fit (const torch::Tensor &X, const torch::Tensor &y, const torch::Tensor &weights, const std::vector< std::string > &featureNames, const std::string &className, const std::map< std::string, std::vector< int > > &states) |
|
void | fit (const torch::Tensor &samples, const torch::Tensor &weights, const std::vector< std::string > &featureNames, const std::string &className, const std::map< std::string, std::vector< int > > &states) |
|
std::vector< int > | predict (const std::vector< std::vector< int > > &) |
|
torch::Tensor | predict (const torch::Tensor &) |
|
torch::Tensor | predict_tensor (const torch::Tensor &samples, const bool proba) |
|
std::vector< std::vector< double > > | predict_proba (const std::vector< std::vector< int > > &) |
|
torch::Tensor | predict_proba (const torch::Tensor &) |
|
double | score (const std::vector< std::vector< int > > &, const std::vector< int > &) |
|
std::vector< std::string > | topological_sort () |
|
std::vector< std::string > | show () const |
|
std::vector< std::string > | graph (const std::string &title) const |
|
void | initialize () |
|
std::string | dump_cpt () const |
|
std::string | version () |
|
Detailed Description
Definition at line 15 of file Network.h.
Constructor & Destructor Documentation
◆ Network() [1/3]
bayesnet::Network::Network |
( |
| ) |
|
◆ Network() [2/3]
bayesnet::Network::Network |
( |
float | maxT | ) |
|
|
explicit |
◆ Network() [3/3]
bayesnet::Network::Network |
( |
const Network & | other | ) |
|
|
explicit |
Member Function Documentation
◆ addEdge()
void bayesnet::Network::addEdge |
( |
const std::string & | parent, |
|
|
const std::string & | child ) |
◆ addNode()
void bayesnet::Network::addNode |
( |
const std::string & | name | ) |
|
◆ dump_cpt()
std::string bayesnet::Network::dump_cpt |
( |
| ) |
const |
◆ fit() [1/3]
void bayesnet::Network::fit |
( |
const std::vector< std::vector< int > > & | input_data, |
|
|
const std::vector< int > & | labels, |
|
|
const std::vector< double > & | weights, |
|
|
const std::vector< std::string > & | featureNames, |
|
|
const std::string & | className, |
|
|
const std::map< std::string, std::vector< int > > & | states ) |
◆ fit() [2/3]
void bayesnet::Network::fit |
( |
const torch::Tensor & | samples, |
|
|
const torch::Tensor & | weights, |
|
|
const std::vector< std::string > & | featureNames, |
|
|
const std::string & | className, |
|
|
const std::map< std::string, std::vector< int > > & | states ) |
◆ fit() [3/3]
void bayesnet::Network::fit |
( |
const torch::Tensor & | X, |
|
|
const torch::Tensor & | y, |
|
|
const torch::Tensor & | weights, |
|
|
const std::vector< std::string > & | featureNames, |
|
|
const std::string & | className, |
|
|
const std::map< std::string, std::vector< int > > & | states ) |
◆ getClassName()
std::string bayesnet::Network::getClassName |
( |
| ) |
const |
◆ getClassNumStates()
int bayesnet::Network::getClassNumStates |
( |
| ) |
const |
◆ getEdges()
std::vector< std::pair< std::string, std::string > > bayesnet::Network::getEdges |
( |
| ) |
const |
◆ getFeatures()
std::vector< std::string > bayesnet::Network::getFeatures |
( |
| ) |
const |
◆ getMaxThreads()
float bayesnet::Network::getMaxThreads |
( |
| ) |
const |
◆ getNodes()
std::map< std::string, std::unique_ptr< Node > > & bayesnet::Network::getNodes |
( |
| ) |
|
◆ getNumEdges()
int bayesnet::Network::getNumEdges |
( |
| ) |
const |
◆ getSamples()
torch::Tensor & bayesnet::Network::getSamples |
( |
| ) |
|
◆ getStates()
int bayesnet::Network::getStates |
( |
| ) |
const |
◆ graph()
std::vector< std::string > bayesnet::Network::graph |
( |
const std::string & | title | ) |
const |
◆ initialize()
void bayesnet::Network::initialize |
( |
| ) |
|
◆ predict() [1/2]
std::vector< int > bayesnet::Network::predict |
( |
const std::vector< std::vector< int > > & | tsamples | ) |
|
◆ predict() [2/2]
torch::Tensor bayesnet::Network::predict |
( |
const torch::Tensor & | samples | ) |
|
◆ predict_proba() [1/2]
std::vector< std::vector< double > > bayesnet::Network::predict_proba |
( |
const std::vector< std::vector< int > > & | tsamples | ) |
|
◆ predict_proba() [2/2]
torch::Tensor bayesnet::Network::predict_proba |
( |
const torch::Tensor & | samples | ) |
|
◆ predict_tensor()
torch::Tensor bayesnet::Network::predict_tensor |
( |
const torch::Tensor & | samples, |
|
|
const bool | proba ) |
◆ score()
double bayesnet::Network::score |
( |
const std::vector< std::vector< int > > & | tsamples, |
|
|
const std::vector< int > & | labels ) |
◆ show()
std::vector< std::string > bayesnet::Network::show |
( |
| ) |
const |
◆ topological_sort()
std::vector< std::string > bayesnet::Network::topological_sort |
( |
| ) |
|
◆ version()
std::string bayesnet::Network::version |
( |
| ) |
|
|
inline |
The documentation for this class was generated from the following files:
- /Users/rmontanana/Code/BayesNet/bayesnet/network/Network.h
- /Users/rmontanana/Code/BayesNet/bayesnet/network/Network.cc