如何複製估算器以便在多個數據集上使用它？

Question

下面是創建兩個數據集的例子：

from sklearn.linear_model import LogisticRegression 
from sklearn.datasets import make_classification 

# data set 1 
X1, y1 = make_classification(n_classes=2, n_features=5, random_state=1) 
# data set 2 
X2, y2 = make_classification(n_classes=2, n_features=5, random_state=2) 

我想用LogisticRegression估計用相同的參數值，以適應設置每個數據的分類：

lr = LogisticRegression() 

clf1 = lr.fit(X1, y1) 
clf2 = lr.fit(X2, y2) 

print "Classifier for data set 1: " 
print " - intercept: ", clf1.intercept_ 
print " - coef_: ", clf1.coef_ 

print "Classifier for data set 2: " 
print " - intercept: ", clf2.intercept_ 
print " - coef_: ", clf2.coef_ 

的問題是這兩個分類是相同的：

Classifier for data set 1: 
    - intercept: [ 0.05191729] 
    - coef_: [[ 0.06704494 0.00137751 -0.12453698 -0.05999127 0.05798146]] 
Classifier for data set 2: 
    - intercept: [ 0.05191729] 
    - coef_: [[ 0.06704494 0.00137751 -0.12453698 -0.05999127 0.05798146]] 

對於這個簡單的例子，我可以使用類似：

lr1 = LogisticRegression() 
lr2 = LogisticRegression() 

clf1 = lr1.fit(X1, y1) 
clf2 = lr2.fit(X2, y2) 

避免該問題。但是，問題依然存在：如何複製/複製一個估計器，並使其具體參數值一般？

Answer 1

from sklearn.base import clone 

lr1 = LogisticRegression() 
lr2 = clone(lr1)