def fn(indexes):
for index in indexes:
if assessment:
scores = gd.assessmentScores(index)
else:
scores = gd.trainingScores(index)
pp.plot(scores, linestyle=':', marker='x', label=legendLabel)
def fn(indexes):
scores = []
for index in indexes:
if assessment:
scores += [gd.assessmentScores(index)]
else:
scores += [gd.trainingScores(index)]
scores = np.array(scores)
averages = np.mean(scores, 0)
pp.plot(averages, linestyle=':', marker='x', label=legendLabel)
def fn(indexes):
scores = []
for index in indexes:
if assessment:
scores += [gd.assessmentScores(index)]
else:
scores += [gd.trainingScores(index)]
scores = np.array(scores)
meanScores = np.mean(scores, 0)
highErrors = np.max(scores, 0) - meanScores
lowErrors = meanScores - np.min(scores, 0)
pp.errorbar(x=[i for i in range(0, len(meanScores))], y=meanScores, yerr=[lowErrors, highErrors], label=legendLabel)