Confusion Matrix, Accuracy, Recall and Precision Demystified скачать в хорошем качестве

Confusion Matrix, Accuracy, Recall and Precision Demystified

This is the first part of a series of two videos In which I want to introduce the main ways by which we evaluate and compare our classification models. In this video, I First explain the possible outcomes of a classifier, then, I cover confusion matrices, along with some classification metrics such as Accuracy, Recall (or Sensitivity), Precision and F1 score. We also make a Superhero detector to arrest these unlawful vigilantes!🦹 📑 Chapters: 0:00 Intro 0:30 Classification 1:20 Classification Possilble Results 2:23 Confusion Matrix 3:36 Accuracy 6:06 Recall 6:30 Precision 6:57 Comparing Classification Metrics 8:34 F1 Score 9:05 Conclusion 🙋‍♂️ Find me on: Find me on: halflingwizard.me 🎁 Support the Channel: If you’d like to support my work, you can check out my wishlist here: https://www.amazon.com/registries/gl/... Your support helps me keep creating content like this. Thank you for being part of this journey! #classification #machine_learning #confusion_matrix #accuracy #recall #precision