Experiment: Change class weights b/c data unbalanced

Results did not appear to change much at all.
Substrates 5 and 9 appear most frequently (look
at confusion matrix results). Thus, set define
class_weight = {5:x, 9:y}.

Setting y to as large as 10^6 and as small as 10^-3
produced at most a 1% difference.

Setting class_weight to 'auto', which sets weights
inversely proportional class frequency, only
produced a 0.1% difference.

Question: why is this so? Data is, in fact,
extremely unbalanced.