代码实现[Python]

# -*- coding: utf-8 -*- 
print(__doc__)

from sklearn.linear_model import LogisticRegression
from sklearn import set_config


lr = LogisticRegression(penalty='l1')
print('Default representation:')
print(lr)
# LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,
#                    intercept_scaling=1, l1_ratio=None, max_iter=100,
#                    multi_class='warn', n_jobs=None, penalty='l1',
#                    random_state=None, solver='warn', tol=0.0001, verbose=0,
#                    warm_start=False)

set_config(print_changed_only=True)
print('\nWith changed_only option:')
print(lr)
# LogisticRegression(penalty='l1')

运行程序

运行时间大约:0分0.003秒。
运行输出的文本内容如下:

Default representation:
LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,
                   intercept_scaling=1, l1_ratio=None, max_iter=100,
                   multi_class='warn', n_jobs=None, penalty='l1',
                   random_state=None, solver='warn', tol=0.0001, verbose=0,
                   warm_start=False)

With changed_only option:
LogisticRegression(penalty='l1')

源码下载

• Python版源码文件: plot_changed_only_pprint_parameter.py
• Jupyter Notebook版源码文件: plot_changed_only_pprint_parameter.ipynb

参考资料

• Compact estimator representations