cleanlab automatically detects problems in a ML dataset. This data-centric AI package facilitates machine learning with messy, real-world data by providing clean labels for robust training and flagging errors in your data
The main idea in the paper is that the performance of regular Multi-layer Perceptron (MLP) can be significantly improved if we use Transformers to transforms regular categorical embeddings into contextual ones.
The TabTransformer is built upon self-attention based Transformers. The Transformer layers transform the embed- dings of categorical features into robust contextual embed- dings to achieve higher prediction accuracy.