SOTAVerified

General Classification

Algorithms trying to solve the general task of classification.

Papers

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Showing 4501–4525 of 14581 papers

TitleStatusHype
Learning Domain Invariant Representations for Child-Adult Classification from Speech—0
Learning Domain Representation for Multi-Domain Sentiment Classification—0
Learning Domain-Sensitive and Sentiment-Aware Word Embeddings—0
Learning Effective Binary Visual Representations with Deep Networks—0
Learning efficient structured dictionary for image classification—0
Learning ELM network weights using linear discriminant analysis—0
Learning Embeddings from Cancer Mutation Sets for Classification Tasks—0
Learning Emotion-enriched Word Representations—0
Learning Euclidean-to-Riemannian Metric for Point-to-Set Classification—0
Learning event representation: As sparse as possible, but not sparser—0
Learning Evolved Combinatorial Symbols with a Neuro-symbolic Generative Model—0
Learning Explainable Linguistic Expressions with Neural Inductive Logic Programming for Sentence Classification—0
Learning Fast and Slow: PROPEDEUTICA for Real-time Malware Detection—0
Learning Feature Engineering for Classification—0
Learning Fine-grained Features via a CNN Tree for Large-scale Classification—0
Learning Fixation Point Strategy for Object Detection and Classification—0
Learning Flexible Classifiers with Shot-CONditional Episodic (SCONE) Training—0
Learning from Adversarial Features for Few-Shot Classification—0
Learning from Counting: Leveraging Temporal Classification for Weakly Supervised Object Localization and Detection—0
Learning from Imbalanced Multiclass Sequential Data Streams Using Dynamically Weighted Conditional Random Fields—0
Learning from Imprecise and Fuzzy Observations: Data Disambiguation through Generalized Loss Minimization—0
Learning from Label Proportions in Brain-Computer Interfaces: Online Unsupervised Learning with Guarantees—0
Learning from Large-scale Noisy Web Data with Ubiquitous Reweighting for Image Classification—0
Learning from LDA using Deep Neural Networks—0
Learning From Less Data: Diversified Subset Selection and Active Learning in Image Classification Tasks—0
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All datasetsXORirisActivityFashion-MNISTISOLETMice ProteinMNISTWine

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