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 821–830 of 3304 papers

TitleStatusHype
A Supervised Geometry-Aware Mapping Approach for Classification of Hyperspectral Images—0
Dimension Reduction of High-Dimensional Datasets Based on Stepwise SVM—0
Deep topic modeling by multilayer bootstrap network and lasso—0
Deep Triphone Embedding Improves Phoneme Recognition—0
Deep Variational Multivariate Information Bottleneck -- A Framework for Variational Losses—0
Deep Variational Sufficient Dimensionality Reduction—0
Classification with Repulsion Tensors: A Case Study on Face Recognition—0
Classification of Schizophrenia from Functional MRI Using Large-scale Extended Granger Causality—0
Defining Reference Sequences for Nocardia Species by Similarity and Clustering Analyses of 16S rRNA Gene Sequence Data—0
An Improvement of PAA on Trend-Based Approximation for Time Series—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