Confusion Matrix in Machine Learning
Classification metric in supervised learning
Published in
4 min readFeb 4, 2021
Why this metric named as confusion matrix? From my point of view, the matrix term refers to row and column, the confusion term refers to the thought of the machine that didn’t classify 100% accurately. Let’s learn about the confusion matrix a little deeper in this article. It is a combined metric of classification to visualize the performance of the model.
The topics we will cover in this article are shown below:
- Confusion matrix
- Type 1 and Type 2 Error
- Accuracy
- Precision
- Recall
- False omission rate
- F1-score
- MCC or phi coefficient
Confusion Matrix
The confusion matrix gives very fruitful information about the predicted performance of the estimator or model that use in machine learning. Let’s see a confusion matrix.
