auto-sklearn是一个自动化的机器学习工具包，是scikit-learn估算器的直接替代品：
>>> import autosklearn.classification >>> cls = autosklearn.classification.AutoSklearnClassifier() >>> cls.fit(X_train, y_train) >>> predictions = cls.predict(X_test)
auto-sklearn使机器学习用户从算法选择和超参数调整中解放出来。 它利用了贝叶斯优化，元学习和集合构造的最新优势。 阅读在NIPS 2015上发表的论文，了解有关auto-sklearn背后技术的更多信息。
>>> import autosklearn.classification >>> import sklearn.model_selection >>> import sklearn.datasets >>> import sklearn.metrics >>> X, y = sklearn.datasets.load_digits(return_X_y=True) >>> X_train, X_test, y_train, y_test = \ sklearn.model_selection.train_test_split(X, y, random_state=1) >>> automl = autosklearn.classification.AutoSklearnClassifier() >>> automl.fit(X_train, y_train) >>> y_hat = automl.predict(X_test) >>> print("Accuracy score", sklearn.metrics.accuracy_score(y_test, y_hat))
