make_classification参数解释

参数 类型 默认 说明
n_samples int类型 可选 (default=100) 样本数量.
n_features int 可选 (default=20) 总的特征数量,是从有信息的数据点,冗余数据点,重复数据点,和特征点-有信息的点-冗余的点-重复点中随机选择的。
n_informative int optional (default=2) informative features数量
n_redundant int optional (default=2) redundant features数量
n_repeated int optional (default=0) duplicated features数量
n_classes int optional (default=2) 类别或者标签数量
n_clusters_per_class int optional (default=2) 每个class中cluster数量
weights floats列表 or None (default=None) 每个类的权重,用于分配样本点
flip_y float optional (default=0.01) 随机交换样本的一段
class_sep float optional (default=1.0) The factor multiplying the hypercube dimension.
hypercube boolean optional (default=True) If True the clusters are put on the vertices of a hypercube. If False,the clusters are put on the vertices of a random polytope.
shift float,array of shape [n_features] or None optional (default=0.0) Shift features by the specified value. If None,then features are shifted by a random value drawn in [-class_sep,class_sep].
scale float array of shape [n_features] or None optional (default=1.0) Multiply features by the specified value. If None,then features are scaled by a random value drawn in [1,100]. Note that scaling happens after shifting.
shuffle boolean optional (default=True) Shuffle the samples and the features.
random_state int,RandomState instance or None optional (default=None) If int,random_state is the seed used by the random number generator; If RandomState instance,random_state is the random number generator; If None,the random number generator is the RandomState instance used by np.random

你可能感兴趣的:(make_classification参数解释)