SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 3051–3060 of 3304 papers

TitleStatusHype
Deep Learning for Efficient GWAS Feature Selection—0
Deep Learning for GWP Prediction: A Framework Using PCA, Quantile Transformation, and Ensemble Modeling—0
Deep Learning for Size and Microscope Feature Extraction and Classification in Oral Cancer: Enhanced Convolution Neural Network—0
Deep Learning in Earthquake Engineering: A Comprehensive Review—0
Deep Learning, Machine Learning, Advancing Big Data Analytics and Management—0
Deep Learning Multidimensional Projections—0
Deep Linear Discriminant Analysis with Variation for Polycystic Ovary Syndrome Classification—0
Deep Manifold Computing and Visualization Using Elastic Locally Isometric Smoothness—0
Deep Manifold Transformation for Nonlinear Dimensionality Reduction—0
Deep matrix factorizations—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