class sklearn.base.
BaseEstimator:为所有的estimators提供基类
方法:
__init__ () |
初始化方法 |
get_params (deep=True) |
获取这个估计器的参数 Parameters: deep : boolean, optional True,将返回该estimator的参数,并包含作为estimator的子对象. Returns:字符串到任意的映射,参数名称映射到它们的取值. |
set_params (**params) |
设置这个estimator的参数 |
class sklearn.base.
TransformerMixin:为所有的transformers提供Mixin class
方法:
__init__ () |
初始化方法 |
fit_transform (X, y=None, **fit_params) |
拟合数据并转换它 Parameters: X : numpy array of shape [n_samples, n_features] y : numpy array of shape [n_samples] Returns: X_new : numpy array of shape [n_samples, n_features_new] |
class sklearn.base.
ClassifierMixin:为所有的classifiers提供Mixin class
__init__ () |
初始化方法 |
score (X, y, sample_weight=None) |
返回给定测试数据和标签的平均度量值 Parameters: X : array-like, shape = (n_samples, n_features) y : array-like, shape = (n_samples) or (n_samples, n_outputs) sample_weight : array-like, shape = [n_samples] |
class sklearn.base.
RegressorMixin:为所有的regression estimators提供Mixin class
__init__ () |
初始化方法 |
score (X, y, sample_weight=None) |
Parameters: X : array-like, shape = (n_samples, n_features) y : array-like, shape = (n_samples) or (n_samples, n_outputs) sample_weight : array-like, shape = [n_samples] |
class sklearn.base.
ClusterMixin:为所有的cluster estimators提供Mixin class
__init__ () |
初始化方法 |
fit_predict (X, y=None) |
Parameters: X : ndarray, shape (n_samples, n_features) Returns:返回聚类的标签 y : ndarray, shape (n_samples,) |