Showing posts with label F1. Show all posts
Showing posts with label F1. Show all posts

Friday, November 4, 2022

Multi-Class Text Classification with a GPT3 Transformer block: An End-to-End Example

 

Multi-Class Text Classification with a GPT3 Transformer block: An End-to-End Example

Author: Murat Karakaya & Cansen Çağlayan
Date created: 05 Oct 2021
Last modified: 19 Oct 2021
Description: This tutorial has 2 parts as explained below. Part A: Data Analysis & Text Preprocessing and Part B: Text Classification. 



                                       Photo by Håkon Grimstad on Unsplash

How to Evaluate a Classifier Trained with an Imbalanced Dataset? Why Accuracy is not Enough?

 

How to Evaluate a Classifier Trained with an Imbalanced Dataset? Why Accuracy is not Enough?

Author: Murat Karakaya
Date created: 19 May 2020
Last modified: 09 Dec 2021
Description: In this tutorial series, we will discuss how to evaluate a classifier trained with an imbalanced dataset. We will see that accuracy metric is not enough to measure the performance of classifiers, especially, when you have an imbalanced dataset. Furthermore, we will implement 8 different classifier models and evaluate their success by comparing the various classification metric results. We will implement the solutions by Python and SciKit Learn library.

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Parts

I will deliver the content in 3 parts:

  • Part A: Fundamentals, Metrics, Synthetic Dataset
  • Part B: Dummy Classifiers, Accuracy, Precision, Recall, F1
  • Part C: ROC, AUC, Worthless Test, Setting up threshold


Photo by Aziz Acharki on Unsplash