A scikit-learn compatible neural network library based on "Revisiting Tabular Deep Learning" (RTDL).
- A scikit-learn compatible package supports 4 neural networks based learning algorithms for tabular data (MLP, ResNet, DCN V2, TabNet, FT-Transformer).
- A scikit-learn compatible package supports automatically identifying categorical features and automatically scaling features to facilitate neural network training.
from sklearn.datasets import load_boston
from sklearn.model_selection import cross_val_score
from rtdl_sklearn.sklearn_models import MLPRegressor
X, y = load_boston(return_X_y=True)
mlp = MLPRegressor()
print(cross_val_score(mlp, X, y, n_jobs=-1))Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please make sure to update tests as appropriate.