#3 Rewrite some tests & remove use_predictions

Remove use_predictions parameter as of now, the model always use it

stree/Strees.py

@@ -126,14 +126,12 @@ class Stree(BaseEstimator, ClassifierMixin):
         random_state: int = None,
         max_depth: int = None,
         tol: float = 1e-4,
-        use_predictions: bool = False,
         min_samples_split: int = 0,
     ):
         self.max_iter = max_iter
         self.C = C
         self.kernel = kernel
         self.random_state = random_state
-        self.use_predictions = use_predictions
         self.max_depth = max_depth
         self.tol = tol
         self.min_samples_split = min_samples_split
@@ -172,6 +170,7 @@ class Stree(BaseEstimator, ClassifierMixin):
         :rtype: list
         """
         up = ~down
+        print(self.kernel, up.shape, down.shape)
         return (
             origin[up[:, 0]] if any(up) else None,
             origin[down[:, 0]] if any(down) else None,
@@ -188,14 +187,7 @@ class Stree(BaseEstimator, ClassifierMixin):
         the hyperplane of the node
         :rtype: np.array
         """
-        if self.use_predictions:
-            res = np.expand_dims(node._clf.decision_function(data), 1)
-        else:
-            # doesn't work with multiclass as each sample has to do inner
-            # product with its own coefficients computes positition of every
-            # sample is w.r.t. the hyperplane
-            res = self._linear_function(data, node)
-        return res
+        return np.expand_dims(node._clf.decision_function(data), 1)
 
     def _split_criteria(self, data: np.array) -> np.array:
         """Set the criteria to split arrays