CommonLit Readability Prize

Rate the complexity of literary passages for grades 3-12 classroom use

Competition webpage

Aim

“In this competition, we’re predicting the reading ease of excerpts from literature. We’ve provided excerpts from several time periods and a wide range of reading ease scores. Note that the test set includes a slightly larger proportion of modern texts (the type of texts we want to generalize to) than the training set.”

Data provided -

Training data

id - unique ID for excerpt
url_legal - URL of source - this is blank in the test set.
license - license of source material - this is blank in the test set.
excerpt - text to predict reading ease of
target - reading ease
standard_error - measure of spread of scores among multiple raters for each excerpt. Not included for test data.

Goal - Predict the final three FVC measurements for each patient, as well as a confidence value in your prediction.

Evaluation metric - root mean squared error. RMSE

Models used -

LightGBM, XGboost, TabNet

Feature engineering and selection

Images