svm - 如何在 SVM 上应用 Word2Vec

Question

我不确定如何让我的训练数据集适应我SVM model的Word2vec训练数据集？我应该question mark在下面的代码中放什么而不是放什​​么？

model = gensim.models.Word2Vec(sentences= df['meaningful_words'])

Train_X, Test_X, Train_Y, Test_Y = model_selection.train_test_split(df['y_labels'],df['meaningful_words'],random_state =1,test_size=0.2)

SVM = svm.SVC(C=1.0, kernel='linear', degree=1, gamma= 'auto')

SVM.fit(??,Train_Y)

predictions_SVM = SVM.predict(Test_X)

print("SVM Accuracy Score",accuracy_score(predictions_SVM, Test_Y)*100)
CONFUSION = confusion_matrix(Test_Y, predictions_SVM)

标签： svmword2vectrain-test-split