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 1061–1070 of 3304 papers

TitleStatusHype
A new band selection approach based on information theory and support vector machine for hyperspectral images reduction and classification—0
Towards a machine learning pipeline in reduced order modelling for inverse problems: neural networks for boundary parametrization, dimensionality reduction and solution manifold approximation—0
Hyperspectral images classification and Dimensionality Reduction using Homogeneity feature and mutual information—0
New wrapper method based on normalized mutual information for dimension reduction and classification of hyperspectral images—0
A Spectral Method for Assessing and Combining Multiple Data VisualizationsCode1
A Novel Approach for Dimensionality Reduction and Classification of Hyperspectral Images based on Normalized Synergy—0
An Algorithm and Heuristic based on Normalized Mutual Information for Dimensionality Reduction and Classification of Hyperspectral images—0
NeuroMapper: In-browser Visualizer for Neural Network TrainingCode0
Face Pyramid Vision TransformerCode0
An Experimental Study of Dimension Reduction Methods on Machine Learning Algorithms with Applications to Psychometrics—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