SOTAVerified

Dimensionality Reduction

Dimensionality reduction is the task of reducing the dimensionality of a dataset.

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Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1821–1830 of 3304 papers

TitleStatusHype
Feature-Preserving Rate-Distortion Optimization in Image Coding for Machines—0
Feature Selection: A perspective on inter-attribute cooperation—0
Feature Selection Based on Orthogonal Constraints and Polygon Area—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
Feature Space Hijacking Attacks against Differentially Private Split Learning—0
Feature Space Sketching for Logistic Regression—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