diff --git a/fern_AxisAligned_regression.png b/fern_AxisAligned_regression.png
new file mode 100644
index 0000000..a8a55d6
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diff --git a/fern_Conic_regression.png b/fern_Conic_regression.png
new file mode 100644
index 0000000..aac675b
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diff --git a/fern_Linear_regression.png b/fern_Linear_regression.png
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index 0000000..f7a208c
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diff --git a/fern_Parabola_regression.png b/fern_Parabola_regression.png
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index 0000000..dd15f92
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diff --git a/randomferns.py b/randomferns.py
index 8c055a5..6f0f32f 100644
--- a/randomferns.py
+++ b/randomferns.py
@@ -15,10 +15,11 @@ def fit( self, points, responses ):
         self.tests = np.array( self.test_class.generate_all( points, self.depth ) )
         if self.regression:
             self.target_dim = responses.shape[1]
-            self.data = np.ones( (2**self.depth, self.target_dim), dtype='float64' )
+            self.data = np.zeros( (2**self.depth, self.target_dim), dtype='float64' )
             bins = self.apply_tests(points)
             bincount = np.bincount(bins, minlength=self.data.shape[0])
-            self.data[self.apply_tests(points)] += responses
+            for dim in range(self.target_dim):
+                self.data[:,dim] += np.bincount(bins, weights=responses[:,dim], minlength=self.data.shape[0])
             self.data[bincount>0] /= bincount[bincount>0][...,np.newaxis]
         else:
             self.n_classes = responses.max() + 1
diff --git a/randomferns_AxisAligned_regression.png b/randomferns_AxisAligned_regression.png
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index 0000000..c063422
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diff --git a/randomferns_Conic_regression.png b/randomferns_Conic_regression.png
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index 0000000..470102e
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diff --git a/randomferns_Linear_regression.png b/randomferns_Linear_regression.png
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index 0000000..08d513c
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diff --git a/randomferns_Parabola_regression.png b/randomferns_Parabola_regression.png
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index 0000000..0b618cb
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