← Questions
Find noisy annotators and retrain a classifier without them
0
I was asked this
No reports yet. Sign in to say where you were asked it.
A classifier is trained on labels from several human annotators, and some of them label carelessly. Find which annotators are unreliable, drop their labels, retrain, and show whether the classifier actually improved. Explain how you would tell a careless annotator from one who simply got harder examples.
No official answer yet. Write yours on the right and run it.
Nothing published yet.
Sign in to submit your code; every attempt is kept here.
Write and test your solution herePython in your browser, the question's tests level by level, every submission kept for you.Sign in to start coding