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 2741–2750 of 3304 papers

TitleStatusHype
An Information Theory-Based Feature Selection Framework for Big Data Under Apache SparkCode0
High-Performance FPGA Implementation of Equivariant Adaptive Separation via Independence Algorithm for Independent Component Analysis—0
Kernel Scaling for Manifold Learning and Classification—0
Kernel Feature Selection via Conditional Covariance MinimizationCode0
Vectorial Dimension Reduction for Tensors Based on Bayesian Inference—0
Dimensionality reduction with missing values imputation—0
Additive Component Analysis—0
Grassmannian Manifold Optimization Assisted Sparse Spectral Clustering—0
Designing Illuminant Spectral Power Distributions for Surface ClassificationCode0
FFTLasso: Large-Scale LASSO in the Fourier Domain—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