SOTAVerified

General Classification

Algorithms trying to solve the general task of classification.

Papers

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Showing 10101–10150 of 14581 papers

TitleStatusHype
Ensembles of phalanxes across assessment metrics for robust ranking of homologous proteins—0
Ensemble Soft-Margin Softmax Loss for Image Classification—0
Ensembling classification models based on phalanxes of variables with applications in drug discovery—0
Ensembling Neural Networks for Digital Pathology Images Classification and Segmentation—0
Entangled q-Convolutional Neural Nets—0
Entanglement and Tensor Networks for Supervised Image Classification—0
Entanglement Entropy of Target Functions for Image Classification and Convolutional Neural Network—0
Entanglement Zoo I: Foundational and Structural Aspects—0
Entanglement Zoo II: Examples in Physics and Cognition—0
Entity-Aware Dependency-Based Deep Graph Attention Network for Comparative Preference Classification—0
Entity-level Classification of Adverse Drug Reactions: a Comparison of Neural Network Models—0
Entity-Specific Sentiment Classification of Yahoo News Comments—0
Entrenamiento de una red neuronal para el reconocimiento de imagenes de lengua de senas capturadas con sensores de profundidad—0
Entropic Graph Regularization in Non-Parametric Semi-Supervised Classification—0
Entropic one-class classifiers—0
Entropy methods for the confidence assessment of probabilistic classification models—0
Environmental sound analysis with mixup based multitask learning and cross-task fusion—0
Environment Sound Classification using Multiple Feature Channels and Attention based Deep Convolutional Neural Network—0
Envy-Free Classification—0
EoANN: Lexical Semantic Relation Classification Using an Ensemble of Artificial Neural Networks—0
Epileptic seizure classification using statistical sampling and a novel feature selection algorithm—0
Episodic CAMN: Contextual Attention-Based Memory Networks With Iterative Feedback for Scene Labeling—0
EPUTION at SemEval-2018 Task 2: Emoji Prediction with User Adaption—0
Equality of Opportunity in Classification: A Causal Approach—0
Equalizing Financial Impact in Supervised Learning—0
Equivalent Classification Mapping for Weakly Supervised Temporal Action Localization—0
Erase or Fill? Deep Joint Recurrent Rain Removal and Reconstruction in Videos—0
Erasing Integrated Learning: A Simple Yet Effective Approach for Weakly Supervised Object Localization—0
Errata: Distant Supervision for Relation Extraction with Matrix Completion—0
Estimating Depth from Monocular Images as Classification Using Deep Fully Convolutional Residual Networks—0
Estimating Maximally Probable Constrained Relations by Mathematical Programming—0
Estimating mutual information in high dimensions via classification error—0
Estimating Posterior Ratio for Classification: Transfer Learning from Probabilistic Perspective—0
Estimating semantic structure for the VQA answer space—0
Estimating Sleep & Work Hours from Alternative Data by Segmented Functional Classification Analysis (SFCA)—0
Estimating the class prior and posterior from noisy positives and unlabeled data—0
Estimating the Fundamental Limits is Easier than Achieving the Fundamental Limits—0
Estimating the Mean Number of K-Means Clusters to Form—0
Estimating the standard error of cross-Validation-Based estimators of classifier performance—0
Estimating Uncertainty Online Against an Adversary—0
Estimating User Communication Styles for Spoken Dialogue Systems—0
Estimation of Classification Rules from Partially Classified Data—0
Estimation of Ground Contacts from Human Gait by a Wearable Inertial Measurement Unit using machine learning—0
\'Etat de l'art : L'influence du domaine sur la classification de l'opinion (State of the Art : Influence of Domain on Opinion Classification) [in French]—0
État de l'art : L'influence du domaine sur la classification de l'opinion (State of the Art : Influence of Domain on Opinion Classification) [in French]—0
ETER : a new metric for the evaluation of hierarchical named entity recognition—0
ETH-DS3Lab at SemEval-2018 Task 7: Effectively Combining Recurrent and Convolutional Neural Networks for Relation Classification and Extraction—0
Evaluating and Boosting Uncertainty Quantification in Classification—0
Evaluating Capability of Deep Neural Networks for Image Classification via Information Plane—0
Evaluating Deep Convolutional Neural Networks for Material Classification—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1KNNAccuracy93.1—Unverified
2RFAccuracy92.96—Unverified
3CARTAccuracy92.82—Unverified
4LDAAccuracy77.22—Unverified
#ModelMetricClaimedVerifiedStatus
1XBNETAccuracy100—Unverified
2MONT3Accuracy100—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy42—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy67.7—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy68.5—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy13.4—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy90.6—Unverified
#ModelMetricClaimedVerifiedStatus
1MONT3Accuracy100—Unverified