SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 1031–1040 of 3304 papers

TitleStatusHype
Angle constrained path to cluster multiple manifolds—0
Chasing Collective Variables using Autoencoders and biased trajectories—0
An Explainable Nature-Inspired Framework for Monkeypox Diagnosis: Xception Features Combined with NGBoost and African Vultures Optimization Algorithm—0
A Comprehensive Filter Feature Selection for Improving Document Classification—0
Efficient Estimation of the Central Mean Subspace via Smoothed Gradient Outer Products—0
Efficient L1-Norm Principal-Component Analysis via Bit Flipping—0
Channel Charting: Locating Users within the Radio Environment using Channel State Information—0
Efficient Binary Embedding of Categorical Data using BinSketch—0
Efficient channel charting via phase-insensitive distance computation—0
Efficient and Scalable Batch Bayesian Optimization Using K-Means—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