Improve Your Classification Models With Threshold Tuning
Last Updated on July 25, 2023 by Editorial Team
Author(s): Edoardo Bianchi
Originally published on Towards AI.
A practical and essential guide
This member-only story is on us. Upgrade to access all of Medium.
Photo by Denisse Leon on Unsplash
Threshold tuning is an important and necessary step in the Data Science pipeline. It is strongly related to the application domain and requires common sense and critical thinking.
Threshold tuning allows you to customize a finished model and adapt it to different needs.
In this article, I will demonstrate how to improve the performance of a model by tuning a decision threshold. Let’s start.
Going beyond AccuracyThe “predict probability” trickChoosing the important metric to maximizeSome real use cases & scenariosHands-on Threshold TuningConclusions
Often, accuracy is not enough to… 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
Towards AI Academy Resources:
We build Enterprise AI. We teach what we learn. 15 AI Experts. 5 practical AI courses. 100k students
Free: 6-day Agentic AI Engineering Email Guide
Get your free Agents Cheatsheet here. Our proven framework for choosing the right AI architecture.
3 years of hands-on work with real clients into 6 pages.
Take our 90+ lesson From Beginner to Advanced LLM Developer Certification: From choosing a project to deploying a working product this is the most comprehensive and practical LLM course out there!
Discover Your Dream AI Career at Towards AI JobsOur jobs board is tailored specifically to AI, Machine Learning and Data Science Jobs and Skills. Explore over 100,000 live AI jobs today with Towards AI Jobs!
Note: Article content contains the views of the contributing authors and not Towards AI.