Complete implementation with tests
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@@ -34,12 +34,8 @@ namespace bayesnet {
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{
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features = features_;
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className = className_;
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// Fills std::vectors Xv & yv with the data from tensors X_ (discretized) & y
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states = fit_local_discretization(y);
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// We have discretized the input data
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// 1st we need to fit the model to build the normal SPODE structure, SPODE::fit initializes the base Bayesian network
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states = iterativeLocalDiscretization(y, static_cast<SPODE*>(this), dataset, features, className, states_, smoothing);
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SPODE::fit(dataset, features, className, states, smoothing);
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states = localDiscretizationProposal(states, model);
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return *this;
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}
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torch::Tensor SPODELd::predict(torch::Tensor& X)
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