SOTAVerified

Multi-class Classification

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.

Papers

Showing 801850 of 903 papers

TitleStatusHype
Scalable Multi-Class Gaussian Process Classification using Expectation Propagation0
Generative-Discriminative Variational Model for Visual Recognition0
Classifying Documents within Multiple Hierarchical Datasets using Multi-Task Learning0
One-step and Two-step Classification for Abusive Language Detection on TwitterCode1
Feature Incay for Representation Regularization0
Semantic Softmax Loss for Zero-Shot Learning0
Learning from Complementary LabelsCode1
Softmax Q-Distribution Estimation for Structured Prediction: A Theoretical Interpretation for RAML0
Comparison of Decision Tree Based Classification Strategies to Detect External Chemical Stimuli from Raw and Filtered Plant Electrical Response0
Every Untrue Label is Untrue in its Own Way: Controlling Error Type with the Log Bilinear LossCode0
Classifying Lexical-semantic Relationships by Exploiting Sense/Concept Representations0
Automatic Detection of Knee Joints and Quantification of Knee Osteoarthritis Severity using Convolutional Neural Networks0
Randomized Kernel Methods for Least-Squares Support Vector Machines0
Computer Aided Detection of Anemia-like Pallor0
DeepNAT: Deep Convolutional Neural Network for Segmenting Neuroanatomy0
Aggressive Sampling for Multi-class to Binary Reduction with Applications to Text ClassificationCode0
GenSVM: A Generalized Multiclass Support Vector MachineCode0
An Asymptotically Optimal Contextual Bandit Algorithm Using Hierarchical Structures0
Hashtag Recommendation Using End-To-End Memory Networks with Hierarchical Attention0
Node-Adapt, Path-Adapt and Tree-Adapt:Model-Transfer Domain Adaptation for Random Forest0
SOL: A Library for Scalable Online Learning AlgorithmsCode1
Big Models for Big Data using Multi objective averaged one dependence estimators0
Simultaneous Learning of Trees and Representations for Extreme Classification and Density Estimation0
Post Selection Inference with Kernels0
A novel online multi-label classifier for high-speed streaming data applications0
A Novel Progressive Learning Technique for Multi-class Classification0
A Novel Online Real-time Classifier for Multi-label Data Streams0
A High Speed Multi-label Classifier based on Extreme Learning Machines0
Multi-Label Classification Method Based on Extreme Learning Machines0
Relational Similarity Machines0
Multi-class classification: mirror descent approach0
Building an Interpretable Recommender via Loss-Preserving Transformation0
How many faces can be recognized? Performance extrapolation for multi-class classification0
Multiple birth least squares support vector machine for multi-class classification0
Efficient Deep Learning for Stereo MatchingCode0
Data-driven root-cause analysis for distributed system anomalies0
Yelp Dataset Challenge: Review Rating Prediction0
Tweet Acts: A Speech Act Classifier for Twitter0
DS-MLR: Exploiting Double Separability for Scaling up Distributed Multinomial Logistic RegressionCode0
Degrees of Freedom in Deep Neural Networks0
A generalized flow for multi-class and binary classification tasks: An Azure ML approach0
Active Learning from Positive and Unlabeled DataCode0
Toward Optimal Feature Selection in Naive Bayes for Text Categorization0
DOLDA - a regularized supervised topic model for high-dimensional multi-class regressionCode0
Discriminative Training of Deep Fully-connected Continuous CRF with Task-specific Loss0
A simple technique for improving multi-class classification with neural networks0
A pragmatic approach to multi-class classification0
Semi-Supervised Zero-Shot Classification With Label Representation Learning0
MANTRA: Minimum Maximum Latent Structural SVM for Image Classification and Ranking0
Convergence rates of sub-sampled Newton methods0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1COVID-CXNetAccuracy (%)94.2Unverified
#ModelMetricClaimedVerifiedStatus
1COVID-ResNetF1 score0.9Unverified
#ModelMetricClaimedVerifiedStatus
1SVM (tficf)Macro F173.9Unverified
#ModelMetricClaimedVerifiedStatus
1Extra TreesF1-Score93.36Unverified
#ModelMetricClaimedVerifiedStatus
1Multi-Model EnsembleMean AUC0.99Unverified