{"library":"pytorch-tabnet","title":"PyTorch TabNet","description":"PyTorch implementation of TabNet (Google's attention-based tabular network). Current version 4.1.0, with semi-annual releases. Supports classification, regression, and unsupervised pre-training.","language":"python","status":"active","last_verified":"Fri May 01","install":{"commands":["pip install pytorch-tabnet"],"cli":null},"imports":["from pytorch_tabnet.tab_model import TabNetClassifier"],"auth":{"required":false,"env_vars":[]},"quickstart":{"code":"from pytorch_tabnet.tab_model import TabNetClassifier\nimport numpy as np\n\nX_train = np.random.rand(100, 10)\ny_train = np.random.randint(0, 2, 100)\n\nclf = TabNetClassifier(device_name='cpu')\nclf.fit(X_train, y_train, max_epochs=10)\nprint(clf.predict(X_train))","lang":"python","description":"Minimal example of fitting a TabNetClassifier on random data.","tag":null,"tag_description":null,"last_tested":null,"results":[]},"compatibility":null}