SOTAVerified

Dimensionality Reduction

Dimensionality reduction is the task of reducing the dimensionality of a dataset.

( Image credit: openTSNE )

Papers

Showing 29012910 of 3304 papers

TitleStatusHype
Deep Learning with Nonparametric ClusteringCode0
Wassmap: Wasserstein Isometric Mapping for Image Manifold LearningCode0
Universal Feature Selection Tool (UniFeat): An Open-Source Tool for Dimensionality ReductionCode0
Enhancing Affinity Propagation for Improved Public Sentiment InsightsCode0
Enhancing Dimension-Reduced Scatter Plots with Class and Feature CentroidsCode0
Bayesian calibration of stochastic agent based model via random forestCode0
Batch-Incremental Triplet Sampling for Training Triplet Networks Using Bayesian Updating TheoremCode0
Self-Taught Convolutional Neural Networks for Short Text ClusteringCode0
Product Manifold LearningCode0
ProgNet: A Transferable Deep Network for Aircraft Engine Damage Propagation Prognosis under Real Flight ConditionsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9Unverified
2tSNEClassification Accuracy51.5Unverified
3IVISClassification Accuracy46.6Unverified
4UMAPClassification Accuracy41.3Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1Unverified
2QSClassification Accuracy68Unverified