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 1291–1300 of 3304 papers

TitleStatusHype
A Novel Approach for Intrinsic Dimension Estimation—0
Feature Selection: A perspective on inter-attribute cooperation—0
Feature Selection Based on Orthogonal Constraints and Polygon Area—0
First-order bifurcation detection for dynamic complex networks—0
Feature Selection for Network Intrusion Detection—0
Feature Selection for Short Text Classification using Wavelet Packet Transform—0
Feature selection in functional data classification with recursive maxima hunting—0
Feature selection or extraction decision process for clustering using PCA and FRSD—0
Feature Selection Using Reinforcement Learning—0
Flashlight Search Medial Axis: A Pixel-Free Pore-Network Extraction Algorithm—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