SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1551–1560 of 3304 papers

TitleStatusHype
Brain Inspired Face Recognition: A Computational Framework—0
ICU Patient Deterioration prediction: a Data-Mining Approach—0
Hybridization of filter and wrapper approaches for the dimensionality reduction and classification of hyperspectral images—0
Hybrid Kronecker Product Decomposition and Approximation—0
Hybrid machine learning models based on physical patterns to accelerate CFD simulations: a short guide on autoregressive models—0
Hybrid quantum-classical classifier based on tensor network and variational quantum circuit—0
Efficient Binary Embedding of Categorical Data using BinSketch—0
Hybrid Quantum-Classical Machine Learning for Sentiment Analysis—0
Hybrid Subspace Learning for High-Dimensional Data—0
Bayesian tomography using polynomial chaos expansion and deep generative networks—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