Multi-class Classification

130 papers with code • 3 benchmarks • 6 datasets

This task has no description! Would you like to contribute one?

Libraries

Use these libraries to find Multi-class Classification models and implementations

Most implemented papers

SentEval: An Evaluation Toolkit for Universal Sentence Representations

facebookresearch/SentEval LREC 2018

We introduce SentEval, a toolkit for evaluating the quality of universal sentence representations.

Evidential Deep Learning to Quantify Classification Uncertainty

labmlai/annotated_deep_learning_paper_implementations NeurIPS 2018

Deterministic neural nets have been shown to learn effective predictors on a wide range of machine learning problems.

Multimodal Speech Emotion Recognition and Ambiguity Resolution

Demfier/multimodal-speech-emotion-recognition 12 Apr 2019

In this work, we adopt a feature-engineering based approach to tackle the task of speech emotion recognition.

Integrated Multi-omics Analysis Using Variational Autoencoders: Application to Pan-cancer Classification

zhangxiaoyu11/OmiVAE 17 Aug 2019

The training procedure of OmiVAE is comprised of an unsupervised phase without the classifier and a supervised phase with the classifier.

Network Representation Learning with Rich Text Information

albertyang33/TADW IJCAI 2015

Representation learning has shown its effectiveness in many tasks such as image classification and text mining.

GenSVM: A Generalized Multiclass Support Vector Machine

GjjvdBurg/GenSVM Journal of Machine Learning Research 2016

Traditional extensions of the binary support vector machine (SVM) to multiclass problems are either heuristics or require solving a large dual optimization problem.

Efficient Set-Valued Prediction in Multi-Class Classification

mwydmuch/napkinXC 19 Jun 2019

In cases of uncertainty, a multi-class classifier preferably returns a set of candidate classes instead of predicting a single class label with little guarantee.

PMLB v1.0: An open source dataset collection for benchmarking machine learning methods

EpistasisLab/pmlb 30 Nov 2020

Motivation: Novel machine learning and statistical modeling studies rely on standardized comparisons to existing methods using well-studied benchmark datasets.

Inverse-Category-Frequency based supervised term weighting scheme for text categorization

zveryansky/textvec 13 Dec 2010

Term weighting schemes often dominate the performance of many classifiers, such as kNN, centroid-based classifier and SVMs.

Fusing Structure and Content via Non-negative Matrix Factorization for Embedding Information Networks

benedekrozemberczki/karateclub arXiv 2018

It is not straightforward to integrate the content of each node in the current state-of-the-art network embedding methods.