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machine-learningclassificationnaivebayesconfusion-matrix
berrak
berrak

Reputation: 68

How to prepare confusion matrix from the predicted class probabilities?

There is a Naive Bayesian classifier which is created with a given training data. In the table, the predicted positive class probabilities and the actual class labels are shown. I want to prepare the confusion matrix but I could not find out how to do it with just knowing the probabilities.

ID Actual class label Predicted positive class probability
1 + 0.6
2 + 0.8
3 - 0.2
4 + 0.3
5 - 0.4

Upvotes: 1

Views: 649

Answers (1)

Vidyadhar Rao
Vidyadhar Rao

Reputation: 333

First, you need to have discrete class labels to compute confusion matrix. Define a threshold on the predicted positive class probability to predict class labels (y_pred). You can then use actual class labels (y_actual) and y_pred to compute the confusion matrix.

from sklearn.metrics import confusion_matrix
confusion_matrix(y_actual, y_pred)

Upvotes: 1

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