{"library":"sppam","title":"sppam","type":"library","description":"A Python library for AUC maximization via a saddle point problem classifier. Current version: 0.1.10, early development stage with occasional releases.","language":"python","status":"active","last_verified":"Sat May 09","install":{"commands":["pip install sppam"],"cli":null},"imports":["from sppam import SPPAM"],"auth":{"required":false,"env_vars":[]},"links":{"homepage":null,"github":"https://github.com/hrolfrc/sppam","docs":null,"changelog":null,"pypi":"https://pypi.org/project/sppam/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null},"quickstart":{"code":"from sppam import SPPAM\nfrom sklearn.datasets import make_classification\nfrom sklearn.model_selection import train_test_split\n\nX, y = make_classification(n_samples=200, weights=[0.9, 0.1], random_state=42)\nX_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=42)\n\nclf = SPPAM()\nclf.fit(X_train, y_train)\nscore = clf.score(X_test, y_test)\nprint(f'AUC: {score:.3f}')","lang":"python","description":"Train an SPPAM classifier on imbalanced synthetic data and evaluate AUC.","tag":null,"tag_description":null,"last_tested":null,"results":[]},"compatibility":null}