Parameter setting that gave the best results on the hold out data(在保持数据上提供最佳结果的参数设置。). scorer_ : function or a dict Scorer function used on the held out data to choose the best parameters for the model. n_splits_ : int The number of cross-validation splits (folds/ite...
#StratifiedKFold#相比于KFold,在进行split的时候需要传入y,并且会根据y的分类,保证分类后y在各个数据集中比例不变,类似于GroupKFold(基于参数groups)importnumpy as npimportpandas as pdfromsklearn.model_selectionimport*fromsklearn.datasetsimportmake_classification SEED= 666 X,y= make_...
ML之sklearn:sklearn.linear_mode中的LogisticRegression函数的简介、使用方法之详细攻略
The Elastic-Net mixing parameter, with ``0 <= l1_ratio <= 1``. Only used if ``penalty='elasticnet'``. Setting ``l1_ratio=0`` is equivalent to using ``penalty='l2'``, while setting ``l1_ratio=1`` is equivalent to using ``penalty='l1'``. For ``0 < l1_ratio <1``, th...
class GridSearchCV Found at: sklearn.model_selection._search class GridSearchCV(BaseSearchCV): """Exhaustive search over specified parameter values for an estimator. Important members are fit, predict.GridSearchCV implements a "fit" and a "score" method. It also implements "predict", "predict...
We discover an inconsistency issue between documentation and code in the class sklearn.linear_model.OrthogonalMatchingPursuit. As mentioned in the description of parameter n_nonzero_coefs and tol. n_nonzero_coefs: int, default=None Desired number of non-zero entries in the solution. If None (...
We discover an inconsistency issue between documentation and code in the class sklearn.linear_model.PassiveAggressiveRegressor. As mentioned in the description of parameter validation_fraction. validation_fraction: float, default=0.1 The proportion of training data to set aside as validation set for ear...
Use NumericalTransformer instead, which takes the function name as a string parameter and hence can be easily serialized.>>> from sklearn_pandas import NumericalTransformer >>> mapper5 = DataFrameMapper([ ... ('children', NumericalTransformer('log')), ... ]) >>> mapper5.fit_transform(...
A step's estimator may be replaced entirely by setting the parameter with its name to another estimator, or a transformer removed by setting it to 'passthrough' or ``None``. 按序激活一连串转换器和结尾的估计器,Pipeline内部的学习器必须是转换器,而且必须可以实现fit和transform方法。
warnings.warn("l1_ratio parameter is only used when penalty is " "'elasticnet'. Got " "(penalty={})". format(self.penalty)) if self.penalty == 'none': if self.C != 1.0: # default values warnings.warn("Setting penalty='none' will ignore the C and ...