Cover Image

Interactive Classification Metrics: A graphical application to build robust intuition for classification model evaluation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Brown, David H., Chicco, Davide
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Provable tradeoffs in adversarially robust classification
by: Dobriban, Edgar, et al.
Published: (2020)

Aligning AI-driven discovery with human intuition
by: Zhang, Kevin, et al.
Published: (2024)

Multiclass threshold-based classification and model evaluation
by: Legnaro, Edoardo, et al.
Published: (2025)

Harnessing intuitive local evolution rules for physical learning
by: Ezraty, Roie, et al.
Published: (2025)

Simulating classification models to evaluate Predict-Then-Optimize methods
by: Smet, Pieter
Published: (2025)

ARMAX identification of low rank graphical models
by: Cao, Wenqi, et al.
Published: (2025)

A metrological framework for uncertainty evaluation in machine learning classification models
by: Bilson, Samuel, et al.
Published: (2025)

Scalable and non-iterative graphical model estimation
by: Khare, Kshitij, et al.
Published: (2024)

No evaluation without fair representation : Impact of label and selection bias on the evaluation, performance and mitigation of classification models
by: Legast, Magali, et al.
Published: (2026)

Selective classification using a robust meta-learning approach
by: Jain, Nishant, et al.
Published: (2022)

Stein's method for marginals on large graphical models
by: Cui, Tiangang, et al.
Published: (2024)

Greedy equivalence search for nonparametric graphical models
by: Aragam, Bryon
Published: (2024)

A robust methodology for long-term sustainability evaluation of Machine Learning models
by: Paz-Ruza, Jorge, et al.
Published: (2025)

Convex estimation of Gaussian graphical regression models with covariates
by: Liu, Ruobin, et al.
Published: (2024)

Delta-AI: Local objectives for amortized inference in sparse graphical models
by: Falet, Jean-Pierre, et al.
Published: (2023)

Nonparametric learning of heterogeneous graphical model on network-linked data
by: Wang, Yuwen, et al.
Published: (2025)

Testing properties of trees in graphical models with covariance queries
by: Burova, Sofiya, et al.
Published: (2026)

Experimental evaluation of offline reinforcement learning for HVAC control in buildings
by: Wang, Jun, et al.
Published: (2024)

Distributionally robust risk evaluation with an isotonic constraint
by: Gui, Yu, et al.
Published: (2024)

Metric properties of partial and robust Gromov-Wasserstein distances
by: Chhoa, Jannatul, et al.
Published: (2024)

Hierarchical confusion matrix for classification performance evaluation
by: Riehl, Kevin, et al.
Published: (2023)

Variational Bayesian surrogate modelling with application to robust design optimisation
by: Archbold, Thomas A., et al.
Published: (2024)

Estimation of partially known Gaussian graphical models with score-based structural priors
by: Sevilla, Martín, et al.
Published: (2024)

Efficient learning of differential network in multi-source non-paranormal graphical models
by: Nikahd, Mojtaba, et al.
Published: (2024)

A unified weighting framework for evaluating nearest neighbour classification
by: Lenz, Oliver Urs, et al.
Published: (2023)

Label-shift robust federated feature screening for high-dimensional classification
by: Qin, Qi, et al.
Published: (2025)

An intuitive rearranging of the Yates covariance decomposition for probabilistic verification of forecasts with the Brier score
by: Vieira, Bruno Hebling
Published: (2026)

A unified framework for evaluating the robustness of machine-learning interpretability for prospect risking
by: Chowdhury, Prithwijit, et al.
Published: (2026)

Learning local neighborhoods of non-Gaussian graphical models: A measure transport approach
by: Liaw, Sarah, et al.
Published: (2025)

A Metric Topology of Deep Learning for Data Classification
by: Wu, Jwo-Yuh, et al.
Published: (2025)

Extremal graphical modeling with latent variables via convex optimization
by: Engelke, Sebastian, et al.
Published: (2024)

RDI: An adversarial robustness evaluation metric for deep neural networks based on model statistical features
by: Song, Jialei, et al.
Published: (2025)

E-ROBOT: a dimension-free method for robust statistics and machine learning via Schrödinger bridge
by: La Vecchia, Davide, et al.
Published: (2025)

Monitoring the calibration of probability forecasts with an application to concept drift detection involving image classification
by: Franck, Christopher T., et al.
Published: (2025)

Understanding team collapse via probabilistic graphical models
by: Nikolaou, Iasonas, et al.
Published: (2024)

AnyLoss: Transforming Classification Metrics into Loss Functions
by: Han, Doheon, et al.
Published: (2024)

Principled Algorithms for Optimizing Generalized Metrics in Binary Classification
by: Mao, Anqi, et al.
Published: (2025)

A conformalized learning of a prediction set with applications to medical imaging classification
by: Hirsch, Roy, et al.
Published: (2024)

Doubly robust nearest neighbors in factor models
by: Dwivedi, Raaz, et al.
Published: (2022)

Inference via robust optimal transportation: theory and methods
by: Ma, Yiming, et al.
Published: (2023)