SOTAVerified

General Classification

Algorithms trying to solve the general task of classification.

Papers

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Showing 3826–3850 of 14581 papers

TitleStatusHype
Correlation and Class Based Block Formation for Improved Structured Dictionary Learning—0
Correlation-Based Method for Sentiment Classification—0
Correlation Clustering with Noisy Partial Information—0
Correlation of Data Reconstruction Error and Shrinkages in Pair-wise Distances under Principal Component Analysis (PCA)—0
Cortical Surface Co-Registration based on MRI Images and Photos—0
COSINE: Compressive Network Embedding on Large-scale Information Networks—0
CoSpace: Common Subspace Learning from Hyperspectral-Multispectral Correspondences—0
A Comparative Study on Polyp Classification using Convolutional Neural Networks—0
Cost-aware Feature Selection for IoT Device Classification—0
Cost-aware Pre-training for Multiclass Cost-sensitive Deep Learning—0
Cost-Based Budget Active Learning for Deep Learning—0
Cost-based Feature Transfer for Vehicle Occupant Classification—0
A Theoretical Analysis of Contrastive Unsupervised Representation Learning—0
Data Augmentation Imbalance For Imbalanced Attribute Classification—0
Cost-Sensitive Approach to Batch Size Adaptation for Gradient Descent—0
Cost-Sensitive BERT for Generalisable Sentence Classification on Imbalanced Data—0
Binary Linear Classification and Feature Selection via Generalized Approximate Message Passing—0
Cost-Sensitive Convolution based Neural Networks for Imbalanced Time-Series Classification—0
Cost-Sensitive Deep Learning with Layer-Wise Cost Estimation—0
Cost-sensitive detection with variational autoencoders for environmental acoustic sensing—0
A Theory on AI Uncertainty Based on Rademacher Complexity and Shannon Entropy—0
Cost Sensitive Learning of Deep Feature Representations from Imbalanced Data—0
Cost-Sensitive Machine Learning Classification for Mass Tuberculosis Verbal Screening—0
Binary disease prediction using tail quantiles of the distribution of continuous biomarkers—0
An Epistemic Approach to the Formal Specification of Statistical Machine Learning—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