训练时的 Python spacy 问题：ValueError：找到具有 0 个特征（形状=（n，0））的数组，而 SVC 需要至少 1 个

Question

我遇到了我的数组不正确的值错误，这非常奇怪，因为我已经确认我的数组不为零。我打印出了每个特征和训练集的“len”。找到具有 0 个特征 (shape=(7, 0)) 的数组，而 SVC 至少需要 1 个特征。我正在使用 spacy 3.4.1 和 python 3.8.10。我究竟做错了什么？

import spacy
from sklearn import svm

nlp = spacy.load("en_core_web_trf")

train_x = [
        "good characters and plot progression", 
        "check out the book", 
        "good story. would recommend", 
        "novel recommendation", 
        "need to make a deposit to the bank", 
        "balance inquiry savings", 
        "save money"
        ]


train_y = [
            "BOOKS", 
            "BOOKS", 
            "BOOKS", 
            "BOOKS", 
            "BANK", 
            "BANK", 
            "BANK", 
            ]


docs = [nlp(text) for text in train_x]
train_x_vectors = [doc.vector for doc in docs]

print (len(train_x_vectors))
print (len(train_y))

clf_svm = svm.SVC(kernel='linear')
clf_svm.fit(train_x_vectors, train_y)

Answer 1

spacy 管道包“en_core_web_trf”没有自带词向量 您需要使用 en_core_web_lg 才能使用“.vector”