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Data Science Academy · Lesson

The Confusion Matrix Decoded

True and false positives and negatives.

Beyond a Single Number

For classifiers, one accuracy score hides too much. The confusion matrix lays out exactly which predictions were right and which were wrong. 🧩

A Simple Grid

The matrix is a small grid: rows are the true classes, columns are the predicted ones. Each cell counts how often that pairing happened.

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

All lessons in this course

  1. Regression Metrics: MAE, MSE, R2
  2. The Confusion Matrix Decoded
  3. Precision, Recall, and F1
  4. ROC, AUC, and Thresholds
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