def create_ml_model(student_id, location):
#Create enough instructor graded submissions that ML will work
for i in xrange(0,settings.MIN_TO_USE_ML):
sub=get_sub("IN",student_id,location, "ML")
sub.state=SubmissionState.finished
sub.save()
grade=get_grader("IN")
grade.submission=sub
grade.save()
# Create ML Model
ml_model_creation.handle_single_location(location)
def create_ml_model(student_id, location):
sub = get_sub("IN", student_id, location, "ML")
sub.state = SubmissionState.finished
sub.save()
pl = PeerLocation(location, student_id)
control = SubmissionControl(pl.latest_submission())
# Create enough instructor graded submissions that ML will work.
for i in xrange(0, control.minimum_to_use_ai):
sub = get_sub("IN", student_id, location, "ML")
sub.state = SubmissionState.finished
sub.save()
grade = get_grader("IN")
grade.submission = sub
grade.save()
# Create ML Model
ml_model_creation.handle_single_location(location)
def create_ml_model(student_id, location):
sub = get_sub("IN",student_id,location, "ML")
sub.state = SubmissionState.finished
sub.save()
pl = PeerLocation(location, student_id)
control = SubmissionControl(pl.latest_submission())
# Create enough instructor graded submissions that ML will work.
for i in xrange(0, control.minimum_to_use_ai):
sub = get_sub("IN", student_id, location, "ML")
sub.state = SubmissionState.finished
sub.save()
grade = get_grader("IN")
grade.submission = sub
grade.save()
# Create ML Model
ml_model_creation.handle_single_location(location)
