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 2311–2320 of 3304 papers

TitleStatusHype
Machine learning in APOGEE: Identification of stellar populations through chemical abundances—0
Machine Learning in LiDAR 3D point clouds—0
Machine learning meets network science: dimensionality reduction for fast and efficient embedding of networks in the hyperbolic space—0
Machine Learning of coarse-grained Molecular Dynamics Force Fields—0
Machine Learning Reveals Composition Dependent Thermal Stability in Halide Perovskites—0
Machine-Learning the Classification of Spacetimes—0
Machine Learning With Feature Selection Using Principal Component Analysis for Malware Detection: A Case Study—0
Macroscopic Market Making Games via Multidimensional Decoupling Field—0
Making Laplacians commute—0
Manifold Approximation by Moving Least-Squares Projection (MMLS)—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