Figure 6 shows an image map of the sound feature vectors and the mean-squared errors after learning. Figure 7 shows the parameter vectors of the training data and the mean-squared error of the parameter estimates after training of the inverse model.\
The mean squared parameter error for the multi-model estimator was
with a variance of 
. The mean outcome error for the
multiple inverse estimator was 
and the variance was 
.
Figure 6: Image map of the outcome errors of the inverse estimator after training.
The upper image shows the feature vectors from the training data and the lower image
shows the square error of the outcome of the distal learning system with respect
to the original feature vectors. Brighter areas indicate higher error.
Figure 7: Image map of the parameter errors of the inverse estimator after training.
The upper image shows the parameter vectors from the training data and the lower
image shows the square error of the estimated parameters with respect to the
original parameter vectors. Brighter areas indicate higher error.