MENTAL MODEL · M4175

Confusion Matrix

DecideHigh supportDecision Science

Included

Version 1.0.0 · Updated 2026-07-28

CORE DEFINITION

In the field of machine learning and statistical classification problems, the confusion matrix (English: confusion matrix) is a visualization tool, especially used in supervised learning, and is generally called a matching matrix in unsupervised learning. Each column of the matrix represents the predicted instances of a class, while each row represents the actual instances of a class. It is named this way because through this matrix, one can easily see whether the machine has confused two different classes (for example, mistaking one class for another). The confusion matrix (also known as an error matrix) is a special type of contingency table with two dimensions (actual and predicted), and both dimensions have the same set of classes.

SCAFFOLDING EFFECT

psychology

Reduce cognitive load

anchor

Anchor fast decisions

A classification model evaluation table: rows/columns represent actual/predicted classes, and cells give TP, FP, FN, TN; from it, accuracy, precision, recall, F1, and AUC can be calculated, revealing error types.

MINIMUM ACTION

In progress 0/4

Practice this model in one real situation:

For the validation set, count the correct and incorrect counts for each class
according to the task, focus on recall or precision
for imbalanced data, look at each class rather than overall accuracy
determine the cost orientation based on FP/FN.

Check to track your progress (stored locally)

Learning progress0%

account_treeGenealogyexpand_more

menu_bookReferencesexpand_more

Source support: Explicit

link
zh.wikipedia.orghttps://zh.wikipedia.org/wiki/%E6%B7%B7%E6%B7%86%E7%9F%A9%E9%98%B5ZH · Explicit
verified

RELATED MODELS