我们从Python开源项目中,提取了以下1个代码示例,用于说明如何使用sklearn.linear_model()。
def get_model_class(method): """ Returns the class associated with a method string. :param method: A string describing the method to use. :return: A class corresponding to the method. """ if method == 'logistic': return sklearn.linear_model.LogisticRegression elif method == 'svm': return sklearn.svm.SVC elif method == 'mirowski-svm': return sklearn.svm.SVC elif method == 'sgd': return sklearn.linear_model.SGDClassifier elif method == 'random-forest': return sklearn.ensemble.RandomForestClassifier elif method == 'nearest-centroid': return sklearn.neighbors.NearestCentroid elif method == 'knn': return sklearn.neighbors.KNeighborsClassifier elif method == 'bagging': return sklearn.ensemble.BaggingClassifier else: raise NotImplementedError("Method {} is not supported".format(method))