title: Tell LabelEnocder to ignore new labels?
body: <p>I'm working with text data where a lot of user error has to be accounted for, eg. there are a lot of cases where upon predicting new data, new labels will occur that the encoder hasn't seen before due to typos etc. I just want to ignore these (so when I run <code>labelencoder.transform(df_newdata['GL_Description'])</code>, I just want it to ignore anything it hasn't seen before). How can I do this? I didn't find a parameter for this in the docs, but is the only way really to check every word one-by-one "by hand" and drop them? Is there a way I can tell the encoder to ignore any new labels that are not in its dictionary?</p>