SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 2371–2380 of 3304 papers

TitleStatusHype
MLPro: A System for Hosting Crowdsourced Machine Learning Challenges for Open-Ended Research Problems—0
MM Algorithms for Distance Covariance based Sufficient Dimension Reduction and Sufficient Variable Selection—0
Mobile Contactless Palmprint Recognition: Use of Multiscale, Multimodel Embeddings—0
Modal Principal Component Analysis—0
Model-based SIR for dimension reduction—0
Model-based targeted dimensionality reduction for neuronal population data—0
Model-Coupled Autoencoder for Time Series Visualisation—0
Model-Free Context-Aware Word Composition—0
Model-free Vehicle Rollover Prevention: A Data-driven Predictive Control Approach—0
Modeling coherence in ESOL learner texts—0
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All datasetsMCAEMNIST

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9—Unverified
2tSNEClassification Accuracy51.5—Unverified
3IVISClassification Accuracy46.6—Unverified
4UMAPClassification Accuracy41.3—Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1—Unverified
2QSClassification Accuracy68—Unverified