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 591–600 of 3304 papers

TitleStatusHype
Nearest Neighbor CCP-Based Molecular Sequence Analysis—0
A semi-supervised learning using over-parameterized regression—0
Optimizing Feature Selection with Genetic Algorithms: A Review of Methods and Applications—0
Application Research On Real-Time Perception Of Device Performance Status—0
The R package psvmSDR: A Unified Algorithm for Sufficient Dimension Reduction via Principal Machines—0
Two-Stage Hierarchical and Explainable Feature Selection Framework for Dimensionality Reduction in Sleep Staging—0
Common Steps in Machine Learning Might Hinder The Explainability Aims in Medicine—0
Investigating Privacy Leakage in Dimensionality Reduction Methods via Reconstruction AttackCode0
Estimating Conditional Average Treatment Effects via Sufficient Representation Learning—0
Self-Adaptive Quantum Kernel Principal Components Analysis for Compact Readout of Chemiresistive Sensor Arrays—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