11/27/2023 0 Comments Confusion matrix![]() Let’s look at an example: A model is used to predict whether a driver will turn left or right at a light. The confusion matrix is used to display how well a model made its predictions. Confusion matrixīoth precision and recall can be interpreted from the confusion matrix, so we start there. Precision, recall, and a confusion matrix…now that’s safer. ![]() ![]() Sometimes, it may give you the wrong impression altogether. With it, you only uncover half the story. You know the model is predicting at about an 86% accuracy because the predictions on your training test said so.īut, 86% is not a good enough accuracy metric. Sometimes the output is right and sometimes it is wrong. You give it your inputs and it gives you an output. So, you’ve built a machine learning model.
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