Fix n components for 3d plot

app.py

@@ -110,7 +110,7 @@ n_labels = labels.max()
 from sklearn import manifold
 
 node_position_model = manifold.LocallyLinearEmbedding(
-    n_components=2, eigen_solver="dense", n_neighbors=6
+    n_components=3, eigen_solver="dense", n_neighbors=6
 )
 
 embedding = node_position_model.fit_transform(X.T).T
@@ -198,5 +198,5 @@ with gr.Blocks(title=title) as demo:
     btn.click(
         visualize_stocks, outputs=gr.Plot(label="Visualizing stock into clusters")
     )
-    gr.Markdown(f"## In progress")
+
 demo.launch()