def do_training(self,epochs=100,test_interval=None):
graph.start_interactive_mode()
errors = []
if test_interval: self.avg_vector_distances = []
for i in range(epochs):
error = 0
for c in self.cases:
error += self.trainer(c)
errors.append(error)
if test_interval: self.consider_interim_test(i,test_interval)
graph.simple_plot(errors,xtitle="Epoch",ytitle="Error",title="")
if test_interval:
graph.newfig()
graph.simple_plot(self.avg_vector_distances,xtitle='Epoch',
ytitle='Avg Hidden-Node Vector Distance',title='')
def autotest(nb=3,nh=2,lr=.1,epochs=100,ti=10):
ac = autoencoder(nb,nh,lr)
graph.newfig()
ac.do_training(epochs,test_interval=ti)
graph.newfig()
return ac.do_testing()