# Metrics for Multi-Class Classification: an Overview

arXiv: https://arxiv.org/abs/2008.05756 · HTML: https://mlsanity.com/paper/2008.05756/

## Key facts

- Cited by 143 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Aug 2020.

## Built on by (most cited first, 30 of 143)

- [Metrics reloaded: Recommendations for image analysis validation](https://mlsanity.com/paper/2206.01653/) (2022)
- [Proteina: Scaling Flow-based Protein Structure Generative Models](https://mlsanity.com/paper/2503.00710/) (2025)
- [Common Limitations of Image Processing Metrics: A Picture Story](https://mlsanity.com/paper/2104.05642/) (2021)
- [Understanding metric-related pitfalls in image analysis validation](https://mlsanity.com/paper/2302.01790/) (2023)
- [A Comprehensive Survey of Agents for Computer Use: Foundations, Challenges, and Future Directions](https://mlsanity.com/paper/2501.16150/) (2025)
- [DRG-LLaMA : Tuning LLaMA Model to Predict Diagnosis-related Group for Hospitalized Patients](https://mlsanity.com/paper/2309.12625/) (2023)
- [A Closer Look at Classification Evaluation Metrics and a Critical Reflection of Common Evaluation Practice](https://mlsanity.com/paper/2404.16958/) (2024)
- [A review of ensemble learning and data augmentation models for class imbalanced problems: combination, implementation and evaluation](https://mlsanity.com/paper/2304.02858/) (2023)
- [Striking the Right Balance: Recall Loss for Semantic Segmentation](https://mlsanity.com/paper/2106.14917/) (2021)
- [Class Binarization to NeuroEvolution for Multiclass Classification](https://mlsanity.com/paper/2308.13876/) (2023)
- [Deep Multimodal Guidance for Medical Image Classification](https://mlsanity.com/paper/2203.05683/) (2022)
- [Automatic Mapping of Unstructured Cyber Threat Intelligence: An Experimental Study](https://mlsanity.com/paper/2208.12144/) (2022)
- [A Topology-aware Graph Coarsening Framework for Continual Graph Learning](https://mlsanity.com/paper/2401.03077/) (2024)
- [Evaluation of an LLM in Identifying Logical Fallacies: A Call for Rigor When Adopting LLMs in HCI Research](https://mlsanity.com/paper/2404.05213/) (2024)
- [Application of federated learning techniques for arrhythmia classification using 12-lead ECG signals](https://mlsanity.com/paper/2208.10993/) (2022)
- [Learning Optimal Fair Scoring Systems for Multi-Class Classification](https://mlsanity.com/paper/2304.05023/) (2023)
- [Systematic comparison of semi-supervised and self-supervised learning for medical image classification](https://mlsanity.com/paper/2307.08919/) (2023)
- [Can Machine Learning Assist in Diagnosis of Primary Immune Thrombocytopenia? A feasibility study](https://mlsanity.com/paper/2405.20562/) (2024)
- [FOLD-RM: A Scalable, Efficient, and Explainable Inductive Learning Algorithm for Multi-Category Classification of Mixed Data](https://mlsanity.com/paper/2202.06913/) (2022)
- [Automated Identification of Eviction Status from Electronic Health Record Notes](https://mlsanity.com/paper/2212.02762/) (2022)
- [Automated multilingual detection of Pro-Kremlin propaganda in newspapers and Telegram posts](https://mlsanity.com/paper/2301.10604/) (2023)
- [Towards Heterogeneous Long-tailed Learning: Benchmarking, Metrics, and Toolbox](https://mlsanity.com/paper/2307.08235/) (2023)
- [The Unreasonable Effectiveness of the Baseline: Discussing SVMs in Legal Text Classification](https://mlsanity.com/paper/2109.07234/) (2021)
- [Benchmark Dataset for Precipitation Forecasting by Post-Processing the Numerical Weather Prediction](https://mlsanity.com/paper/2206.15241/) (2022)
- [Probably Approximately Precision and Recall Learning](https://mlsanity.com/paper/2411.13029/) (2024)
- [Pearson-Matthews correlation coefficients for binary and multinary classification and hypothesis testing](https://mlsanity.com/paper/2305.05974/) (2023)
- [SampleLLM: Optimizing Tabular Data Synthesis in Recommendations](https://mlsanity.com/paper/2501.16125/) (2025)
- [The role of data partitioning on the performance of EEG-based deep learning models in supervised cross-subject analysis: a preliminary study](https://mlsanity.com/paper/2505.13021/) (2025)
- [Under-bagging Nearest Neighbors for Imbalanced Classification](https://mlsanity.com/paper/2109.00531/) (2021)
- [A Vision Transformer-Based Approach to Bearing Fault Classification via Vibration Signals](https://mlsanity.com/paper/2208.07070/) (2022)

## Abstract (arXiv)

Classification tasks in machine learning involving more than two classes are known by the name of "multi-class classification". Performance indicators are very useful when the aim is to evaluate and compare different classification models or machine learning techniques. Many metrics come in handy to test the ability of a multi-class classifier. Those metrics turn out to be useful at different stage of the development process, e.g. comparing the performance of two different models or analysing the behaviour of the same model by tuning different parameters. In this white paper we review a list of the most promising multi-class metrics, we highlight their advantages and disadvantages and show their possible usages during the development of a classification model.