linearRegression()返回列表中的列表(sklearn) [英] linearRegression() returns list within list (sklearn)

问题描述

我正在Python中进行多元线性回归( sklearn )，但是由于某些原因，这些系数未正确返回为列表.而是返回列表"IN A LIST":

I'm doing multivariate linear regression in Python (sklearn), but for some reason, the coefficients are not correctly returned as a list. Instead, a list IN A LIST is returned:

from sklearn import linear_model
clf = linear_model.LinearRegression()
# clf.fit ([[0, 0, 0], [1, 1, 1], [2, 2, 2]], [0, 1, 2])
clf.fit([[394, 3878, 13, 4, 0, 0],[384, 10175, 14, 4, 0, 0]],[3,9])
print 'coef array',clf.coef_
print 'length', len(clf.coef_)
print 'getting value 0:', clf.coef_[0]
print 'getting value 1:', clf.coef_[1]

这将返回列表[[]]而不是列表[]中的值.知道为什么会这样吗?输出:

This returns the values in a list of a list [[]] instead of a list []. Any idea why this is happening? Output:

coef array [[  1.03428648e-03   9.54477167e-04   1.45135995e-07   0.00000000e+00
0.00000000e+00   0.00000000e+00]]
length 1
getting value 0: [  1.03428648e-03   9.54477167e-04   1.45135995e-07   0.0000000
0e+00 0.00000000e+00   0.00000000e+00]
getting value 1:
Traceback (most recent call last):
  File "regress.py", line 8, in <module>
    print 'getting value 1:', clf.coef_[1]
IndexError: index out of bounds

但这可行:

from sklearn import linear_model
clf = linear_model.LinearRegression()
clf.fit ([[0, 0, 0], [1, 1, 1], [2, 2, 2]], [0, 1, 2])
# clf.fit([[394, 3878, 13, 4, 0, 0],[384, 10175, 14, 4, 0, 0]],[3,9])
print 'coef array',clf.coef_
print 'length', len(clf.coef_)
print 'getting value 0:', clf.coef_[0]
print 'getting value 1:', clf.coef_[1]

输出:

coef array [ 0.33333333  0.33333333  0.33333333]
length 3
getting value 0: 0.333333333333
getting value 1: 0.333333333333

推荐答案

此问题已通过更新SciKit-Learn文件夹中的两个文件来解决.

This is fixed by updating two files in the SciKit-Learn folder.

代码在这里: https://github.com/scikit-learn/scikit-learn/commit/d0b20f0a21b42b853

这篇关于linearRegression()返回列表中的列表(sklearn)的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！