Update writeup

_code/pset_11/cwm.py

@@ -139,8 +139,8 @@ def em_step():
         predicted = np.array([cluster_func(x[n], m) for n in range(N)])
         out_var[m] = cw_expectation((y - predicted)**2.0, m) + tiny
 
-make_plot(plot_name(0))
 print_everything()
+make_plot(plot_name(0))
 for i in range(50):
     em_step()
     make_plot(plot_name(i + 1))

_psets/11.md

@@ -14,8 +14,12 @@ during the EM iterations.
 
 My code lives [here](https://gitlab.cba.mit.edu/erik/nmm_2020_site/-/tree/master/_code/pset_11).
 
-Here's a video of the convergence progress with three clusters.
+Here's a video of 50 EM iterations with three clusters. I'm displaying the local linear models over
+a $$4 \sigma$$ range. (I don't indicate the output variance in any way, would be nice to add this.)
 
 <video width="480" height="320" controls="controls" muted plays-inline>
 <source type="video/mp4" src="../assets/mp4/11_cwm.mp4">
 </video>
+
+Not surprisingly, for tanh three clusters seems to work best. Any less and the fit degrades, any
+more and some clusters end up with needlessly similar local models.