SOTAVerified

General Classification

Algorithms trying to solve the general task of classification.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1751–1775 of 14581 papers

TitleStatusHype
Comparing Classification Models on Kepler Data—0
LightLayers: Parameter Efficient Dense and Convolutional Layers for Image ClassificationCode0
Large-Scale Extended Granger Causality for Classification of Marijuana Users From Functional MRI—0
To do or not to do: cost-sensitive causal decision-making—0
One vs Previous and Similar Classes Learning -- A Comparative Study—0
Fixed-MAML for Few Shot Classification in Multilingual Speech Emotion RecognitionCode0
A Symmetric Loss Perspective of Reliable Machine Learning—0
A unifying approach on bias and variance analysis for classification—0
Towards Network Traffic Monitoring Using Deep Transfer Learning—0
Fast Ensemble Learning Using Adversarially-Generated Restricted Boltzmann MachinesCode0
A Novel Bio-Inspired Hybrid Multi-Filter Wrapper Gene Selection Method with Ensemble Classifier for Microarray Data—0
Explainable Neural Network-based Modulation Classification via Concept Bottleneck Models—0
In-Ear SpO2 for Classification of Cognitive Workload—0
Learning Neural Networks on SVD Boosted Latent Spaces for Semantic ClassificationCode0
An Evolution of CNN Object Classifiers on Low-Resolution Images—0
Multi-label Ranking: Mining Multi-label and Label Ranking Data—0
Multitask Learning for Class-Imbalanced Discourse Classification—0
One-class Classification Robust to Geometric Transformation—0
Adaptive Stacked Graph Filter—0
Neural Disjunctive Normal Form: Vertically Integrating Logic With Deep Learning For Classification—0
Near-Optimal Glimpse Sequences for Training Hard Attention Neural Networks—0
Graph-Graph Similarity Network—0
Brain Tumor Detection and Classification based on Hybrid Ensemble Classifier—0
AC-VAE: Learning Semantic Representation with VAE for Adaptive Clustering—0
Maximum Categorical Cross Entropy (MCCE): A noise-robust alternative loss function to mitigate racial bias in Convolutional Neural Networks (CNNs) by reducing overfitting—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
1MONT3Accuracy100—Unverified
2XBNETAccuracy100—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy42—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy67.7—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy68.5—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy13.4—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy90.6—Unverified
#ModelMetricClaimedVerifiedStatus
1MONT3Accuracy100—Unverified