Copertina

MLMC: Interactive multi-label multi-classifier evaluation without confusion matrices

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Doknic, Aleksandar, Möller, Torsten
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

The Multiplex Classification Framework: optimizing multi-label classifiers through problem transformation, ontology engineering, and model ensembling
di: Offidani, Mauro Nievas, et al.
Pubblicazione: (2024)

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

Leveraging Nested MLMC for Sequential Neural Posterior Estimation with Intractable Likelihoods
di: Yang, Xiliang, et al.
Pubblicazione: (2024)

MLMC-based Resource Adequacy Assessment with Active Learning Trained Surrogate Models
di: Zhang, Ruiqi, et al.
Pubblicazione: (2025)

Hoeffding adaptive trees for multi-label classification on data streams
di: Esteban, Aurora, et al.
Pubblicazione: (2024)

Ranking hierarchical multi-label classification results with mLPRs
di: Ye, Yuting, et al.
Pubblicazione: (2022)

Consistent algorithms for multi-label classification with macro-at-$k$ metrics
di: Schultheis, Erik, et al.
Pubblicazione: (2024)

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

Exploring label correlations using decision templates for ensemble of classifier chains
di: Rocha, Victor F., et al.
Pubblicazione: (2026)

Benchmarking Uncertainty and its Disentanglement in multi-label Chest X-Ray Classification
di: Baur, Simon, et al.
Pubblicazione: (2025)

GNN-MultiFix: Addressing the pitfalls for GNNs for multi-label node classification
di: Zhao, Tianqi, et al.
Pubblicazione: (2024)

Generalized test utilities for long-tail performance in extreme multi-label classification
di: Schultheis, Erik, et al.
Pubblicazione: (2023)

Cost-constrained multi-label group feature selection using shadow features
di: Klonecki, Tomasz, et al.
Pubblicazione: (2024)

Improving the evaluation of samplers on multi-modal targets
di: Grenioux, Louis, et al.
Pubblicazione: (2025)

Comparison of spectrogram scaling in multi-label Music Genre Recognition
di: Karpiński, Bartosz, et al.
Pubblicazione: (2025)

Online hierarchical partitioning of the output space in extreme multi-label data stream
di: Neves, Lara, et al.
Pubblicazione: (2025)

Explainable machine learning multi-label classification of Spanish legal judgements
di: de Arriba-Pérez, Francisco, et al.
Pubblicazione: (2024)

Efficient multi-prompt evaluation of LLMs
di: Polo, Felipe Maia, et al.
Pubblicazione: (2024)

A dual ensemble classifier used to recognise contaminated multi-channel EMG and MMG signals in the control of upper limb bioprosthesis
di: Trajdos, Pawel, et al.
Pubblicazione: (2024)

FRAME-C: A knowledge-augmented deep learning pipeline for classifying multi-electrode array electrophysiological signals
di: Ranasinghe, Nisal, et al.
Pubblicazione: (2025)

COPA: Comparing the incomparable in multi-objective model evaluation
di: Javaloy, Adrián, et al.
Pubblicazione: (2025)

Exploring space efficiency in a tree-based linear model for extreme multi-label classification
di: Lin, He-Zhe, et al.
Pubblicazione: (2024)

$F_β$-plot -- a visual tool for evaluating imbalanced data classifiers
di: Wojciechowski, Szymon, et al.
Pubblicazione: (2024)

I-trustworthy Models. A framework for trustworthiness evaluation of probabilistic classifiers
di: Vashistha, Ritwik, et al.
Pubblicazione: (2025)

Low-power multi-mode fiber projector overcomes shallow neural networks classifiers
di: Ancora, Daniele, et al.
Pubblicazione: (2022)

SSDLabeler: Realistic semi-synthetic data generation for multi-label artifact classification in EEG
di: Akama, Taketo, et al.
Pubblicazione: (2025)

Fusion-ResNet: A Lightweight multi-label NILM Model Using PCA-ICA Feature Fusion
di: Hoosh, Sahar Moghimian, et al.
Pubblicazione: (2025)

Fundamental limits of community detection from multi-view data: multi-layer, dynamic and partially labeled block models
di: Yang, Xiaodong, et al.
Pubblicazione: (2024)

Identifying birdsong syllables without labelled data
di: Teng, Mélisande, et al.
Pubblicazione: (2025)

Deep adaptive sampling for surrogate modeling without labeled data
di: Wang, Xili, et al.
Pubblicazione: (2024)

Statistical multi-metric evaluation and visualization of LLM system predictive performance
di: Ackerman, Samuel, et al.
Pubblicazione: (2025)

Interpretable temporal fusion network of multi- and multi-class arrhythmia classification
di: Kim, Yun Kwan
Pubblicazione: (2025)

A tutorial on multi-view autoencoders using the multi-view-AE library
di: Aguila, Ana Lawry, et al.
Pubblicazione: (2024)

A practical approach to evaluating the adversarial distance for machine learning classifiers
di: Siedel, Georg, et al.
Pubblicazione: (2024)

A practical PINN framework for multi-scale problems with multi-magnitude loss terms
di: Wang, Yong, et al.
Pubblicazione: (2023)

ACT-JEPA: Novel Joint-Embedding Predictive Architecture for Efficient Policy Representation Learning
di: Vujinovic, Aleksandar, et al.
Pubblicazione: (2025)

FuseSampleAgg: Fused Neighbor Sampling and Aggregation for Mini-batch GNNs
di: Stanković, Aleksandar
Pubblicazione: (2025)

Reconstruction of dynamical systems from data without time labels
di: Zeng, Zhijun, et al.
Pubblicazione: (2023)

AutoSAGE: Input-Aware CUDA Scheduling for Sparse GNN Aggregation (SpMM/SDDMM) and CSR Attention
di: Stankovic, Aleksandar
Pubblicazione: (2025)

Nonlinear multi-study factor analysis
di: Moran, Gemma E., et al.
Pubblicazione: (2026)