confusion-matrix

Vocabulary Word

Definition

A 'confusion matrix' is like a report card for a machine learning model. It tells us what the machine got right and what it got wrong. It's a table with counts of true positives, false positives, true negatives, and false negatives.

Examples in Different Contexts

In machine learning, the confusion matrix is crucial for evaluating the effectiveness of algorithms in categorizing data. A machine learning engineer might state, 'Using the confusion matrix, we can identify areas where our algorithm needs improvement.'

Practice Scenarios

Academics

Scenario:

I believe our research is showing promising results. However, we need to cross-check the accuracy and ensure what we are reporting is correct.

Response:

Agree, presenting a confusion matrix could give a quantitative measure of our study's accuracy and direct future improvements.

Business

Scenario:

The number of flagged transactions in our system seems off. It's possible the algorithm could be over-marking or some transactions might escape.

Response:

I agree. Maybe we should generate a confusion matrix to assess the accuracy of our fraud detection system.