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 1771–1780 of 3304 papers

TitleStatusHype
Performance Improvement of Path Planning algorithms with Deep Learning Encoder Model—0
Performance of Johnson-Lindenstrauss Transform for k-Means and k-Medians Clustering—0
Performance prediction of data streams on high-performance architecture—0
Permutation invariant functions: statistical tests, density estimation, and computationally efficient embedding—0
Personalising Mobile Advertising Based on Users Installed Apps—0
Persuasion by Dimension Reduction—0
Perturbation Bounds for Procrustes, Classical Scaling, and Trilateration, with Applications to Manifold Learning—0
PFAx: Predictable Feature Analysis to Perform Control—0
Pharmacoprint -- a combination of pharmacophore fingerprint and artificial intelligence as a tool for computer-aided drug design—0
Phone-based Metric as a Predictor for Basic Personality Traits—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