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 2061–2070 of 3304 papers

TitleStatusHype
Improving information retrieval through correspondence analysis instead of latent semantic analysis—0
Improving Lexical Semantics for Sentential Semantics: Modeling Selectional Preference and Similar Words in a Latent Variable Model—0
Improving Oral Cancer Outcomes Through Machine Learning and Dimensionality Reduction—0
Improving Problem Identification via Automated Log Clustering using Dimensionality Reduction—0
Improving Sparse Representation-Based Classification Using Local Principal Component Analysis—0
Improving the generalization of network based relative pose regression: dimension reduction as a regularizer—0
Improving the Projection of Global Structures in Data through Spanning Trees—0
Improving Triplet-Based Channel Charting on Distributed Massive MIMO Measurements—0
Imputation of Time-varying Edge Flows in Graphs by Multilinear Kernel Regression and Manifold Learning—0
IMU-based Modularized Wearable Device for Human Motion Classification—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