(2)将noise设置为0.1,factor设置为0.5 我们发现这个noise设置的越大,那么噪声就越大,factor设置的越大,两个环就越近。 3、make_classification() sklearn.datasets.make_classification(n_samples=100,n_features=20,n_informative=2, n_redundant=2,n_repeated=0,n_classes=2, n_clusters_per_class=2, weig...
make_classification: a more intricate variant """generator = check_random_state(random_state)ifisinstance(centers, numbers.Integral): centers = generator.uniform(center_box[0], center_box[1], size=(centers, n_features))else: centers = check_array(centers) n_features = centers.shape[1]ifisin...
scikit-learn（简称sklearn）是一个广泛使用的Python机器学习库，它提供了丰富的功能和工具，用于数据挖掘...
the random number generator is the RandomState instance usedby `np.random`.Returns---X : array of shape [n_samples, n_features]The generated samples.y : array of shape [n_samples]The integer labels for cluster membership of each sample.Examples--->>> from sklearn.datasets.samples_generator...