Multi-class Classification
195 papers with code • 4 benchmarks • 10 datasets
Libraries
Use these libraries to find Multi-class Classification models and implementationsDatasets
Most implemented papers
SentEval: An Evaluation Toolkit for Universal Sentence Representations
We introduce SentEval, a toolkit for evaluating the quality of universal sentence representations.
Evidential Deep Learning to Quantify Classification Uncertainty
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
In this work, we adopt a feature-engineering based approach to tackle the task of speech emotion recognition.
Efficient Deep Learning for Stereo Matching
In the past year, convolutional neural networks have been shown to perform extremely well for stereo estimation.
Efficient Set-Valued Prediction in Multi-Class Classification
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.
Integrated Multi-omics Analysis Using Variational Autoencoders: Application to Pan-cancer Classification
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
Representation learning has shown its effectiveness in many tasks such as image classification and text mining.
GenSVM: A Generalized Multiclass Support Vector Machine
Traditional extensions of the binary support vector machine (SVM) to multiclass problems are either heuristics or require solving a large dual optimization problem.
PMLB v1.0: An open source dataset collection for benchmarking machine learning methods
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
Term weighting schemes often dominate the performance of many classifiers, such as kNN, centroid-based classifier and SVMs.