F1 Score: A Visual Guide — And Why It Won’t Save You From Imbalanced Data

Author(s): Vlastimil Martinek

Originally published on Towards AI.

TL;DR at the end

Photo by Lightscape on Unsplash

This member-only story is on us. Upgrade to access all of Medium.

Our job is to create a model to classify if people are healthy or sick. We are given data about them, we’ve created multiple classification models, and it’s time to select the best one.

A common way to estimate a model's performance is to measure its precision and recall.

Precision — What portion of all predicted positives are actual positives.

Recall — what portion of all actual positives in our data did we predict correctly.

Precision and recall are great metrics, but they’re still two numbers. If you want… Read the full blog for free on Medium.

Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.

Published via Towards AI