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Set smoothing as fit parameter

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This commit is contained in:
Ricardo Montañana Gómez
2024-06-11 11:40:45 +02:00
parent 27a3e5a5e0
commit b34869cc61
30 changed files with 168 additions and 178 deletions
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4
bayesnet/classifiers/KDBLd.cc
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@@ -8,7 +8,7 @@
namespace bayesnet {
KDBLd::KDBLd(int k) : KDB(k), Proposal(dataset, features, className) {}
KDBLd& KDBLd::fit(torch::Tensor& X_, torch::Tensor& y_, const std::vector<std::string>& features_, const std::string& className_, map<std::string, std::vector<int>>& states_)
KDBLd& KDBLd::fit(torch::Tensor& X_, torch::Tensor& y_, const std::vector<std::string>& features_, const std::string& className_, map<std::string, std::vector<int>>& states_, const Smoothing_t smoothing)
{
checkInput(X_, y_);
features = features_;
@@ -19,7 +19,7 @@ namespace bayesnet {
states = fit_local_discretization(y);
// We have discretized the input data
// 1st we need to fit the model to build the normal KDB structure, KDB::fit initializes the base Bayesian network
KDB::fit(dataset, features, className, states);
KDB::fit(dataset, features, className, states, smoothing);
states = localDiscretizationProposal(states, model);
return *this;
}