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from sklearn.pipeline import Pipeline
model = Pipeline([('vectorizer',tvec),('classifier',clf2)])
model.fit(IV_train, DV_train)
from sklearn.metrics import confusion_matrix
predictions = model.predict(IV_test)
confusion_matrix(predictions, DV_test)

I want to know what the confusion matrix line in the code does.

desertnaut
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John
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    Have you looked at the documentation of the function? https://scikit-learn.org/stable/modules/generated/sklearn.metrics.confusion_matrix.html Is there a specific line in the documentation that you struggle with? – Itai Dagan Apr 30 '22 at 14:03
  • in my case is y_true DV_test and y_pred predictions? – John Apr 30 '22 at 14:17
  • A confusion matrix contains the accuracy of your model, comparing the prediction with the ground truth. – scmanjarrez Apr 30 '22 at 14:36

1 Answers1

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A confusion matrix is a tabular summary of the number of correct and incorrect predictions made by a classifier. https://www.educative.io/edpresso/how-to-create-a-confusion-matrix-in-python-using-scikit-learn

a python learner
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