python logistic 多标签_LogisticRegression：未知标签类型：在python中使用sklearn’连续’...

我有以下代码来测试一些最流行的sklearn python库的ML算法：

import numpy as np

from sklearn import metrics, svm

from sklearn.linear_model import LinearRegression

from sklearn.linear_model import LogisticRegression

from sklearn.tree import DecisionTreeClassifier

from sklearn.neighbors import KNeighborsClassifier

from sklearn.discriminant_analysis import LinearDiscriminantAnalysis

from sklearn.naive_bayes import GaussianNB

from sklearn.svm import SVC

trainingData = np.array([ [2.3, 4.3, 2.5], [1.3, 5.2, 5.2], [3.3, 2.9, 0.8], [3.1, 4.3, 4.0] ])

trainingScores = np.array( [3.4, 7.5, 4.5, 1.6] )

predictionData = np.array([ [2.5, 2.4, 2.7], [2.7, 3.2, 1.2] ])

clf = LinearRegression()

clf.fit(trainingData, trainingScores)

print("LinearRegression")

print(clf.predict(predictionData))

clf = svm.SVR()

clf.fit(trainingData, trainingScores)

print("SVR")

print(clf.predict(predictionData))

clf = LogisticRegression()

clf.fit(trainingData, trainingScores)

print("LogisticRegression")

print(clf.predict(predictionData))

clf = DecisionTreeClassifier()

clf.fit(trainingData, trainingScores)

print("DecisionTreeClassifier")

print(clf.predict(predictionData))

clf = KNeighborsClassifier()

clf.fit(trainingData, trainingScores)

print("KNeighborsClassifier")

print(clf.predict(predictionData))

clf = LinearDiscriminantAnalysis()

clf.fit(trainingData, trainingScores)

print("LinearDiscriminantAnalysis")

print(clf.predict(predictionData))

clf = GaussianNB()

clf.fit(trainingData, trainingScores)

print("GaussianNB")

print(clf.predict(predictionData))

clf = SVC()

clf.fit(trainingData, trainingScores)

print("SVC")

print(clf.predict(predictionData))

前两个工作正常,但我在LogisticRegression调用中遇到以下错误：

root@ubupc1:/home/ouhma# python stack.py

LinearRegression

[ 15.72023529 6.46666667]

SVR

[ 3.95570063 4.23426243]

Traceback (most recent call last):

File "stack.py", line 28, in

clf.fit(trainingData, trainingScores)

File "/usr/local/lib/python2.7/dist-packages/sklearn/linear_model/logistic.py", line 1174, in fit

check_classification_targets(y)

File "/usr/local/lib/python2.7/dist-packages/sklearn/utils/multiclass.py", line 172, in check_classification_targets

raise ValueError("Unknown label type: %r" % y_type)

ValueError: Unknown label type: 'continuous'

输入数据与之前的调用相同,那么这里发生了什么？

顺便说一句,为什么在LinearRegression()和SVR()算法的第一次预测中存在巨大的差异(15.72对3.95)？