ReviewFrontiers in computational neuroscience2014
How to evaluate an agent's behavior to infrequent events?-Reliable performance estimation insensitive to class distribution.
Review in Frontiers in computational neuroscience, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- PToPI: A Comprehensive Review, Analysis, and Knowledge Representation of Binary Classification Performance Measures/Metrics.SN computer science · 2023Article
- Vigilance to Painful Laser Stimuli is Associated with Increased State Anxiety and Tense Arousal.Journal of pain research · 2023Article
- Single-Option P300-BCI Performance Is Affected by Visual Stimulation Conditions.Sensors (Basel, Switzerland) · 2020Article
- Optimization of convolutional neural network hyperparameters for automatic classification of adult mosquitoes.PloS one · 2020Article
- Empirical Comparison of Distributed Source Localization Methods for Single-Trial Detection of Movement Preparation.Frontiers in human neuroscience · 2018Article
- Multi-Tasking and Choice of Training Data Influencing Parietal ERP Expression and Single-Trial Detection-Relevance for Neuroscience and Clinical Applications.Frontiers in neuroscience · 2018Article
- CANcer-specific Evaluation System (CANES): a high-accuracy platform, for preclinical single/multi-biomarker discovery.Oncotarget · 2017Article
- A Hybrid FPGA-Based System for EEG- and EMG-Based Online Movement Prediction.Sensors (Basel, Switzerland) · 2017Article
- An Intelligent Man-Machine Interface-Multi-Robot Control Adapted for Task Engagement Based on Single-Trial Detectability of P300.Frontiers in human neuroscience · 2016Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In everyday life, humans and animals often have to base decisions on infrequent relevant stimuli with respect to frequent irrelevant ones. When research in neuroscience mimics this situation, the effect of this imbalance in stimulus classes on performance evaluation has to be considered. This is most obvious for the often used overall accuracy, because the proportion of correct responses is governed by the more frequent class. This imbalance problem has been widely debated across disciplines and out of the discussed treatments this review focusses on performance estimation. For this, a more universal view is taken: an agent performing a classification task. Commonly used performance measures are characterized when used with imbalanced classes. Metrics like Accuracy, F-Measure, Matthews Correlation Coefficient, and Mutual Information are affected by imbalance, while other metrics do not have this drawback, like AUC, d-prime, Balanced Accuracy, Weighted Accuracy and G-Mean. It is pointed out that one is not restricted to this group of metrics, but the sensitivity to the class ratio has to be kept in mind for a proper choice. Selecting an appropriate metric is critical to avoid drawing misled conclusions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.