diff --git a/yli/regress.py b/yli/regress.py
index 9290335..f0ae850 100644
--- a/yli/regress.py
+++ b/yli/regress.py
@@ -663,9 +663,9 @@ class RegressionModel:
 				params.extend(s.beta.point for s in term.categories.values())
 		
 		explainer = shap.LinearExplainer((np.array(params[1:]), params[0]), xdata, **kwargs)  # FIXME: Assumes zeroth term is intercept
-		shap_values = explainer.shap_values(xdata).astype('float')
+		explanation = explainer(xdata)
 		
-		return ShapResult(weakref.ref(self), shap_values, list(xdata.columns))
+		return ShapResult(weakref.ref(self), explanation)
 
 class LikelihoodRatioTestResult(ChiSquaredResult):
 	"""
diff --git a/yli/shap.py b/yli/shap.py
index 6119f46..41ef085 100644
--- a/yli/shap.py
+++ b/yli/shap.py
@@ -26,10 +26,9 @@ class ShapResult:
 	See :meth:`yli.regress.RegressionModel.shap`.
 	"""
 	
-	def __init__(self, model, shap_values, features):
+	def __init__(self, model, explanation):
 		self.model = model
-		self.shap_values = shap_values
-		self.features = features
+		self.explanation = explanation
 	
 	@staticmethod
 	def _get_xdata(model):
@@ -64,7 +63,8 @@ class ShapResult:
 		:rtype: Series
 		"""
 		
-		return pd.Series(abs(self.shap_values).mean(axis=0), index=self.features)
+		raise NotImplementedError()
+		#return pd.Series(abs(self.shap_values).mean(axis=0), index=self.features)
 	
 	def plot(self, **kwargs):
 		"""
@@ -82,14 +82,6 @@ class ShapResult:
 		if model is None:
 			raise Exception('Referenced RegressionModel has been dropped')
 		
-		xdata = self._get_xdata(model)
-		
-		shap.summary_plot(self.shap_values, xdata, show=False, axis_color='black', **kwargs)  # pass show=False to get gcf/gca
-		
-		# Fix colour bar
-		# https://stackoverflow.com/questions/70461753/shap-the-color-bar-is-not-displayed-in-the-summary-plot
-		ax_colorbar = plt.gcf().axes[-1]
-		ax_colorbar.set_aspect('auto')
-		ax_colorbar.set_box_aspect(50)
+		shap.plots.beeswarm(self.explanation, show=False, axis_color='black', max_display=None, **kwargs)  # pass show=False to get gcf/gca
 		
 		return plt.gcf(), plt.gca()