如何在 sklearn Pipeline 的 RobustScaler 中调整 quantile_range？

Question

pipeline = Pipeline([
                     ('scale', RobustScaler(quantile_range=()))
                     ('classify', OneVsRestClassifier(SVC()))
                      ],
                     memory=self.memory)

鉴于该管道，如何使用 GridSearchCV 调整 RobustScaler 中的 quantile_range？默认 quantile_range 是 (25.0, 75.0)。我想尝试的替代方案是 (5.0, 95.0), (10.0, 90.0), ..., (25.0, 75.0)。如何实现？我想，params_grid 应该是这样的：

params_grid = [{'scale__quantile_range': ??}]

但是我不知道在问号占位符中放什么。

Answer 1

要尝试的超参数应该是可迭代的。尝试：

from sklearn.preprocessing import RobustScaler
from sklearn.pipeline import Pipeline
from sklearn.multiclass import OneVsRestClassifier
from sklearn.svm import SVC
from sklearn.model_selection import GridSearchCV
from sklearn.datasets import make_classification

pipeline = Pipeline([
                     ('scale', RobustScaler(quantile_range=())),
                     ('classify', OneVsRestClassifier(SVC()))
                      ],
                     memory=None)

params = {"scale__quantile_range":[(25.0,75.0),(10.0,90.0),(1.0,99.0)]}

grid_cf = GridSearchCV(pipeline, param_grid=params)

X,y = make_classification(1000,10,n_classes=2,random_state=42)

grid_cf.fit(X,y)

grid_cf.best_params_

{'scale__quantile_range': (1.0, 99.0)}

如何在 sklearn Pipeline 的 RobustScaler 中调整 quantile_range？

How to tune quantile_range in RobustScaler in sklearn Pipeline?

python-3.x

machine-learning

scikit-learn

gridsearchcv