Question

我有两个变量X和Y。

X的结构（即np.array）：

Usage

$ lerna bootstrap
Bootstrap the packages in the current Lerna repo. Installs all of their dependencies and links any cross-dependencies.

When run, this command will:

npm install all external dependencies of each package.
Symlink together all Lerna packages that are dependencies of each other.
npm run prepublish in all bootstrapped packages (unless --ignore-prepublish is passed).
npm run prepare in all bootstrapped packages.

Y的结构：

prepublish

Y中的数组，例如[1252，26777，26831]是三个单独的特征。

我正在使用scikit学习模块中的Knn分类器

[[26777 24918 26821 ...    -1    -1    -1]
[26777 26831 26832 ...    -1    -1    -1]
[26777 24918 26821 ...    -1    -1    -1]
...
[26811 26832 26813 ...    -1    -1    -1]
[26830 26831 26832 ...    -1    -1    -1]
[26830 26831 26832 ...    -1    -1    -1]]

但是我收到一条错误消息：

ValueError：不支持multiclass-multioutput

我猜不支持'Y'的结构，为了使程序执行我需要进行哪些更改？

输入：

[[1252, 26777, 26831], [1252, 26777, 26831], [1252, 26777, 26831], [1252, 26777, 26831], [1252, 26777, 26831], [1252, 26777, 26831], [25197, 26777, 26781], [25197, 26777, 26781], [25197, 26777, 26781], [26764, 25803, 26781], [26764, 25803, 26781], [25197, 26777, 26781], [25197, 26777, 26781], [1252, 26777, 16172], [1252, 26777, 16172]]

预期输出：

classifier = KNeighborsClassifier(n_neighbors=3)
classifier.fit(X,Y)
predictions = classifier.predict(X)
print(accuracy_score(Y,predictions))

Answer 1

如错误所述，KNN不支持多输出回归/分类。

对于您的问题，您需要MultiOutputClassifier()。

from sklearn.multioutput import MultiOutputClassifier

knn = KNeighborsClassifier(n_neighbors=3)
classifier = MultiOutputClassifier(knn, n_jobs=-1)
classifier.fit(X,Y)

工作示例：

>>> from sklearn.feature_extraction.text import TfidfVectorizer
>>> corpus = [
...     'This is the first document.',
...     'This document is the second document.',
...     'And this is the third one.',
...     'Is this the first document?',
... ]
>>> vectorizer = TfidfVectorizer()
>>> X = vectorizer.fit_transform(corpus)

>>> Y = [[124323,1234132,1234],[124323,4132,14],[1,4132,1234],[1,4132,14]]

>>> from sklearn.multioutput import MultiOutputClassifier
>>> from sklearn.neighbors import KNeighborsClassifier
>>> knn = KNeighborsClassifier(n_neighbors=3)
>>> classifier = MultiOutputClassifier(knn, n_jobs=-1)
>>> classifier.fit(X,Y)
>>> predictions = classifier.predict(X)

array([[124323,   4132,     14],
       [124323,   4132,     14],
       [     1,   4132,   1234],
       [124323,   4132,     14]])

>>> classifier.score(X,np.array(Y))
0.5

>>> test_data = ['I want to test this']
>>> classifier.predict(vectorizer.transform(test_data))
array([[124323,   4132,     14]])

“不支持Multiclass-multioutput” Scikit中的学习Knn分类器错误

1 个答案: