Refactor version method in PyClassifier

src/BayesNet/AODELd.cc

@@ -1,5 +1,4 @@
 #include "AODELd.h"
-#include "Models.h"
 
 namespace bayesnet {
     AODELd::AODELd() : Ensemble(), Proposal(dataset, features, className) {}

src/PyClassifiers/PyClassifier.cc

@@ -2,7 +2,7 @@
 namespace pywrap {
     namespace bp = boost::python;
     namespace np = boost::python::numpy;
-    PyClassifier::PyClassifier(const std::string& module, const std::string& className) : module(module), className(className), fitted(false)
+    PyClassifier::PyClassifier(const std::string& module, const std::string& className, bool sklearn) : module(module), className(className), sklearn(sklearn), fitted(false)
     {
         // This id allows to have more than one instance of the same module/class
         id = reinterpret_cast<clfId_t>(this);
@@ -29,12 +29,11 @@ namespace pywrap {
     }
     std::string PyClassifier::version()
     {
+        if (sklearn) {
+            return pyWrap->sklearnVersion();
+        }
         return pyWrap->version(id);
     }
-    std::string PyClassifier::sklearnVersion()
-    {
-        return pyWrap->sklearnVersion();
-    }
     std::string PyClassifier::callMethodString(const std::string& method)
     {
         return pyWrap->callMethodString(id, method);

src/PyClassifiers/PyClassifier.h

@@ -15,7 +15,7 @@
 namespace pywrap {
     class PyClassifier : public bayesnet::BaseClassifier {
     public:
-        PyClassifier(const std::string& module, const std::string& className);
+        PyClassifier(const std::string& module, const std::string& className, const bool sklearn = false);
         virtual ~PyClassifier();
         PyClassifier& fit(std::vector<std::vector<int>>& X, std::vector<int>& y, const std::vector<std::string>& features, const std::string& className, std::map<std::string, std::vector<int>>& states) override { return *this; };
         // X is nxm tensor, y is nx1 tensor
@@ -29,7 +29,6 @@ namespace pywrap {
         float score(torch::Tensor& X, torch::Tensor& y) override;
         void setHyperparameters(nlohmann::json& hyperparameters) override;
         std::string version();
-        std::string sklearnVersion();
         std::string callMethodString(const std::string& method);
         std::string getVersion() override { return this->version(); };
         int getNumberOfNodes()const override { return 0; };
@@ -48,6 +47,7 @@ namespace pywrap {
         PyWrap* pyWrap;
         std::string module;
         std::string className;
+        bool sklearn;
         clfId_t id;
         bool fitted;
     };

src/PyClassifiers/RandomForest.cc

@@ -1,8 +1,11 @@
 #include "RandomForest.h"
 
 namespace pywrap {
-    std::string RandomForest::version()
+    void RandomForest::setHyperparameters(nlohmann::json& hyperparameters)
     {
-        return sklearnVersion();
+        // Check if hyperparameters are valid
+        const std::vector<std::string> validKeys = { "n_estimators", "n_jobs", "random_state" };
+        checkHyperparameters(validKeys, hyperparameters);
+        this->hyperparameters = hyperparameters;
     }
 } /* namespace pywrap */

src/PyClassifiers/RandomForest.h

@@ -5,9 +5,9 @@
 namespace pywrap {
     class RandomForest : public PyClassifier {
     public:
-        RandomForest() : PyClassifier("sklearn.ensemble", "RandomForestClassifier") {};
+        RandomForest() : PyClassifier("sklearn.ensemble", "RandomForestClassifier", true) {};
         ~RandomForest() = default;
-        std::string version();
+        void setHyperparameters(nlohmann::json& hyperparameters) override;
     };
 } /* namespace pywrap */
 #endif /* RANDOMFOREST_H */

src/PyClassifiers/SVC.cc

@@ -1,10 +1,6 @@
 #include "SVC.h"
 
 namespace pywrap {
-    std::string SVC::version()
-    {
-        return sklearnVersion();
-    }
     void SVC::setHyperparameters(nlohmann::json& hyperparameters)
     {
         // Check if hyperparameters are valid

src/PyClassifiers/SVC.h

@@ -5,9 +5,8 @@
 namespace pywrap {
     class SVC : public PyClassifier {
     public:
-        SVC() : PyClassifier("sklearn.svm", "SVC") {};
+        SVC() : PyClassifier("sklearn.svm", "SVC", true) {};
         ~SVC() = default;
-        std::string version();
         void setHyperparameters(nlohmann::json& hyperparameters) override;
     };