SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 2691–2700 of 3304 papers

TitleStatusHype
Toward Scalable Machine Learning and Data Mining: the Bioinformatics Case—0
Understanding a Version of Multivariate Symmetric Uncertainty to assist in Feature SelectionCode0
Tensor-Based Classifiers for Hyperspectral Data Analysis—0
On Principal Components Regression, Random Projections, and Column Subsampling—0
Lazy stochastic principal component analysisCode0
Near Optimal Sketching of Low-Rank Tensor Regression—0
Bayesian nonparametric Principal Component Analysis—0
Representation Learning on Graphs: Methods and Applications—0
An Algorithmic Information Calculus for Causal Discovery and Reprogramming Systems—0
Transform Invariant Auto-encoder—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