SOTAVerified

General Classification

Algorithms trying to solve the general task of classification.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 7676–7700 of 14581 papers

TitleStatusHype
One-class Classification Robust to Geometric Transformation—0
One-Class Classification: Taxonomy of Study and Review of Techniques—0
One-Class Feature Learning Using Intra-Class Splitting—0
One-Class Semi-Supervised Learning: Detecting Linearly Separable Class by its Mean—0
One-Class SVM with Privileged Information and its Application to Malware Detection—0
Augmenting Variational Autoencoders with Sparse Labels: A Unified Framework for Unsupervised, Semi-(un)supervised, and Supervised Learning—0
One-Shot Image Classification by Learning to Restore Prototypes—0
One-Shot learning based classification for segregation of plastic waste—0
One-shot learning by inverting a compositional causal process—0
One-Shot Learning using Mixture of Variational Autoencoders: a Generalization Learning approach—0
One-Shot Learning with Triplet Loss for Vegetation Classification Tasks—0
One Size Fits All? A simple LSTM for non-literal token and construction-level classification—0
One-Step or Two-Step Optimization and the Overfitting Phenomenon: A Case Study on Time Series Classification—0
One-step regression and classification with crosspoint resistive memory arrays—0
On evaluating CNN representations for low resource medical image classification—0
On Evaluating the Quality of Rule-Based Classification Systems—0
One-vs-All Models for Asynchronous Training: An Empirical Analysis—0
One-vs-Each Approximation to Softmax for Scalable Estimation of Probabilities—0
One-vs-Each Approximation to Softmax for Scalable Estimation of Probabilities—0
One-vs.-One Mitigation of Intersectional Bias: A General Method to Extend Fairness-Aware Binary Classification—0
One vs Previous and Similar Classes Learning -- A Comparative Study—0
On Expected Accuracy—0
On Extending Neural Networks with Loss Ensembles for Text Classification—0
Interpretable feature subset selection: A Shapley value based approach—0
On Flat versus Hierarchical Classification in Large-Scale Taxonomies—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