address review comments

README.md

@@ -43,7 +43,7 @@ pip install m2cgen
 |  | Classification | Regression |
 | --- | --- | --- |
 | **Linear** | <ul><li>scikit-learn<ul><li>LogisticRegression</li><li>LogisticRegressionCV</li><li>PassiveAggressiveClassifier</li><li>Perceptron</li><li>RidgeClassifier</li><li>RidgeClassifierCV</li><li>SGDClassifier</li></ul></li><li>lightning<ul><li>AdaGradClassifier</li><li>CDClassifier</li><li>FistaClassifier</li><li>SAGAClassifier</li><li>SAGClassifier</li><li>SDCAClassifier</li><li>SGDClassifier</li></ul></li></ul> | <ul><li>scikit-learn<ul><li>ARDRegression</li><li>BayesianRidge</li><li>ElasticNet</li><li>ElasticNetCV</li><li>HuberRegressor</li><li>Lars</li><li>LarsCV</li><li>Lasso</li><li>LassoCV</li><li>LassoLars</li><li>LassoLarsCV</li><li>LassoLarsIC</li><li>LinearRegression</li><li>OrthogonalMatchingPursuit</li><li>OrthogonalMatchingPursuitCV</li><li>PassiveAggressiveRegressor</li><li>RANSACRegressor(only supported regression estimators can be used as a base estimator)</li><li>Ridge</li><li>RidgeCV</li><li>SGDRegressor</li><li>TheilSenRegressor</li></ul><li>StatsModels<ul><li>Generalized Least Squares (GLS)</li><li>Generalized Least Squares with AR Errors (GLSAR)</li><li>Ordinary Least Squares (OLS)</li><li>Quantile Regression (QuantReg)</li><li>Weighted Least Squares (WLS)</li></ul><li>lightning<ul><li>AdaGradRegressor</li><li>CDRegressor</li><li>FistaRegressor</li><li>SAGARegressor</li><li>SAGRegressor</li><li>SDCARegressor</li></ul></li></ul> |
-| **SVM** | <ul><li>scikit-learn<ul><li>LinearSVC</li><li>NuSVC</li><li>SVC</li></ul></li><li>lightning<ul><li>KernelSVC</li><li>LinearSVC</li></ul></li></ul> | <ul><li>scikit-learn<ul><li>LinearSVR</li><li>NuSVR</li><li>SVR</li></ul></li><li>lightning<ul><li>LinearSVR</li></ul></li></ul> |
+| **SVM** | <ul><li>scikit-learn<ul><li>LinearSVC</li><li>NuSVC</li><li>SVC</li></ul></li><li>lightning<ul><li>KernelSVC (binary only, multiclass is not supported yet)</li><li>LinearSVC</li></ul></li></ul> | <ul><li>scikit-learn<ul><li>LinearSVR</li><li>NuSVR</li><li>SVR</li></ul></li><li>lightning<ul><li>LinearSVR</li></ul></li></ul> |
 | **Tree** | <ul><li>DecisionTreeClassifier</li><li>ExtraTreeClassifier</li></ul> | <ul><li>DecisionTreeRegressor</li><li>ExtraTreeRegressor</li></ul> |
 | **Random Forest** | <ul><li>ExtraTreesClassifier</li><li>LGBMClassifier(rf booster only)</li><li>RandomForestClassifier</li><li>XGBRFClassifier(binary only, multiclass is not supported yet)</li></ul> | <ul><li>ExtraTreesRegressor</li><li>LGBMRegressor(rf booster only)</li><li>RandomForestRegressor</li><li>XGBRFRegressor</li></ul> |
 | **Boosting** | <ul><li>LGBMClassifier(gbdt/dart/goss booster only)</li><li>XGBClassifier(gbtree/gblinear booster only)</li><ul> | <ul><li>LGBMRegressor(gbdt/dart/goss booster only)</li><li>XGBRegressor(gbtree/gblinear booster only)</li></ul> |

m2cgen/assemblers/svm.py

@@ -54,7 +54,12 @@ def _apply_kernel(self, support_vectors, to_reuse=False):
         return kernel_exprs
 
     def _get_supported_kernels(self):
-        return {}
+        return {
+            "rbf": self._rbf_kernel,
+            "sigmoid": self._sigmoid_kernel,
+            "poly": self._poly_kernel,
+            "linear": self._linear_kernel
+        }
 
     def _get_gamma(self):
         raise NotImplementedError
@@ -74,14 +79,6 @@ def _get_single_intercept(self):
 
 class SklearnSVMModelAssembler(BaseSVMModelAssembler):
 
-    def _get_supported_kernels(self):
-        return {
-            "rbf": self._rbf_kernel,
-            "sigmoid": self._sigmoid_kernel,
-            "poly": self._poly_kernel,
-            "linear": self._linear_kernel
-        }
-
     def _get_gamma(self):
         return self.model._gamma
 

tests/test_ast.py

@@ -45,6 +45,7 @@ def test_count_all_exprs_types():
         ast.BinVectorExpr(
             ast.VectorVal([
                 ast.ExpExpr(ast.NumVal(2)),
+                ast.SqrtExpr(ast.NumVal(2)),
                 ast.PowExpr(ast.NumVal(2), ast.NumVal(3)),
                 ast.TanhExpr(ast.NumVal(1)),
                 ast.BinNumExpr(
@@ -67,4 +68,4 @@ def test_count_all_exprs_types():
             )),
         ast.BinNumOpType.MUL)
 
-    assert ast.count_exprs(expr) == 24
+    assert ast.count_exprs(expr) == 25