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Multi-class Classification

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Multi-class classification is a type of supervised learning where the goal is to assign an input to one of three or more distinct classes. Unlike binary classification (which has only two classes), multi-class classification handles multiple labels and uses algorithms like logistic regression, decision trees, random forests, SVMs, or neural networks to predict the correct category based on the features of the input data.

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/cjyaras/normalized-neural-collapse

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Neural Collapse with Normalized Features: A Geometric Analysis over the Riemannian Manifold

https://github.com/coastalcph/lex-glue

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LexGLUE: A Benchmark Dataset for Legal Language Understanding in English

https://github.com/coderbak/psvm

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$p$SVM: Soft-margin SVMs with $p$-norm Hinge Loss

https://github.com/cvillacampa/GPInputNoise

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Multi-class Gaussian Process Classification with Noisy Inputs

https://github.com/deeplearning-wisc/multi-label-ood

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Can multi-label classification networks know what they don't know?

https://github.com/devd1092/ood-skin-lesion

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Out-of-Distribution Detection for Long-tailed and Fine-grained Skin Lesion Images

https://github.com/devmotion/CalibrationPaper

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Calibration tests in multi-class classification: A unifying framework

https://github.com/devmotion/calibration_iclr2021

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Calibration tests beyond classification

https://github.com/dialogue-evaluation/ruatd

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Findings of the The RuATD Shared Task 2022 on Artificial Text Detection in Russian

https://github.com/discovershu/SoRR

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Learning by Minimizing the Sum of Ranked Range

https://github.com/doribear/A-Novel-Patent-Similarity-Measurement-Methodology

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A Novel Patent Similarity Measurement Methodology: Semantic Distance and Technological Distance

https://github.com/drmuskangarg/cams

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Explainable Causal Analysis of Mental Health on Social Media Data

https://github.com/ds4ai-upb/ml4gw

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Efficient Machine Learning Ensemble Methods for Detecting Gravitational Wave Glitches in LIGO Time Series

https://github.com/esla/multilabelfy

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Leveraging Human-Machine Interactions for Computer Vision Dataset Quality Enhancement

https://github.com/facebookresearch/InvarianceUnitTests

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Invariant-Feature Subspace Recovery: A New Class of Provable Domain Generalization Algorithms

https://github.com/facebookresearch/SentEval

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SentEval: An Evaluation Toolkit for Universal Sentence Representations

https://github.com/falsenegativelab/mlscorecheck

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Enumerating the k-fold configurations in multi-class classification problems

https://github.com/fdbtrs/Unsupervised-Face-Recognition-using-Unlabeled-Synthetic-Data

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Unsupervised Face Recognition using Unlabeled Synthetic Data

https://github.com/fdbtrs/sface-privacy-friendly-and-accurate-face-recognition-using-synthetic-data

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SFace: Privacy-friendly and Accurate Face Recognition using Synthetic Data

https://github.com/fengbeiliu/semi-chest

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Self-supervised Mean Teacher for Semi-supervised Chest X-ray Classification

https://github.com/flowfrontiers/cyberml-dataquality

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Evaluating ML-Based Anomaly Detection Across Datasets of Varied Integrity: A Case Study

https://github.com/frenchkrab/is2023-powerset-diarization

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Powerset multi-class cross entropy loss for neural speaker diarization

https://github.com/furyton/csrec

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Learning Robust Sequential Recommenders through Confident Soft Labels

https://github.com/future-mobility-lab/bi-level-framework

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Incident duration prediction using a bi-level machine learning framework with outlier removal and intra-extra joint optimisation

https://github.com/gaa-uam/c-gb

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Condensed Gradient Boosting

https://github.com/gentaiscool/few-shot-lm

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Language Models are Few-shot Multilingual Learners

https://github.com/giuliotosato/autokeras-bioacustic

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Auto deep learning for bioacoustic signals

https://github.com/google/uncertainty-baselines

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Exploring the Uncertainty Properties of Neural Networks' Implicit Priors in the Infinite-Width Limit

https://github.com/google/yggdrasil-decision-forests

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Relationships are Complicated! An Analysis of Relationships Between Datasets on the Web

https://github.com/guangyizhangbci/eeg_riemannian

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Spatio-Temporal EEG Representation Learning on Riemannian Manifold and Euclidean Space

https://github.com/guglielmocamporese/hands-segmentation-pytorch

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VISTA: Vision Transformer enhanced by U-Net and Image Colorfulness Frame Filtration for Automatic Retail Checkout

https://github.com/guoyurong0104/crl-code

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Competing Ratio Loss for Discriminative Multi-class Image Classification

https://github.com/hajimesuzuki999/qpf-bic

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Application of Quantum Pre-Processing Filter for Binary Image Classification with Small Samples

https://github.com/hans66hsu/gats

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What Makes Graph Neural Networks Miscalibrated?

https://github.com/hanxudong/systematic_evaluation_of_predictive_fairness

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Systematic Evaluation of Predictive Fairness

https://github.com/haziqj/iprior-interaction

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Additive interaction modelling using I-priors

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