# PinSage model

NOTE: this version is not using NodeFlow yet.
      
This example only work with Python 3.6+

First, download and extract from https://data.dgl.ai/dataset/ml-1m.tar.gz

One can then run the following to train PinSage on MovieLens-1M:

```bash
python3 main.py --opt Adam --lr 1e-3
```

One can also incorporate user and movie features into training:

```bash
python3 main.py --opt Adam --lr 1e-3 --use-feature
```

Currently, performance of PinSage on MovieLens-1M has the best mean reciprocal rank of
0.032298±0.048078 on validation (and 0.033695±0.051963 on test set for the same model).
The Implicit Factorization Model from Spotlight has a 0.034572±0.041653 on the test set.
