SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 2631–2640 of 3304 papers

TitleStatusHype
An Adaptive Dimension Reduction Estimation Method for High-dimensional Bayesian Optimization—0
An Algorithm and Heuristic based on Normalized Mutual Information for Dimensionality Reduction and Classification of Hyperspectral images—0
An Algorithmic Information Calculus for Causal Discovery and Reprogramming Systems—0
Analyse en Composante Principale pour l'extraction des i-vecteurs en v\'erification du locuteur (Principal Component Analysis for i-vector extraction in speaker verification.) [in French]—0
Analysing race and sex bias in brain age prediction—0
Analysis and mining of low-carbon and energy-saving tourism data characteristics based on machine learning algorithm—0
Analysis and Visualization of Deep Neural Networks in Device-Free Wi-Fi Indoor Localization—0
Analysis of Cellular Feature Differences of Astrocytomas with Distinct Mutational Profiles Using Digitized Histopathology Images—0
Analysis of Evolving Cortical Neuronal Networks Using Visual Informatics—0
Analytic Bilinear Appearance Subspace Construction for Modeling Image Irradiance under Natural Illumination and Non-Lambertian Reflectance—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