xiaosu200/wm001

What it does

This project is a classification model for e-commerce orders. It puts each order into one of two buckets: normal orders (real purchases) or brushing orders (fake orders placed to inflate a seller's ratings).

What 'brushing' means

In online marketplaces, a seller sometimes creates fake orders — paying people or bots to buy their products — so the order count and reviews look better than they are. Those are 'brushing' orders. Spotting them is a way to keep the marketplace fair.

How the model works (based on the README)

The README only says it 'distinguishes normal orders and brushing orders'. It doesn't describe the input features, algorithm, or training data. So beyond saying it is a binary classification model — one label for normal, one for brushing — the technical details are not available from the project description.

What you can't infer

• The model's accuracy or performance.
• What signals it uses (price, frequency, IP address, etc.).
• Whether it was trained on real marketplace data or synthetic data.
• How to run or deploy it.

The README is a one-line summary. If you need implementation details, you'd have to inspect the code repository itself.