SOTAVerified

Dimensionality Reduction

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

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Papers

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Showing 641–650 of 3304 papers

TitleStatusHype
Comparison among dimensionality reduction techniques based on Random Projection for cancer classification—0
Comparison of feature extraction and dimensionality reduction methods for single channel extracellular spike sorting—0
Comparison of Machine Learning Models in Food Authentication Studies—0
Comparison of Methods in Skin Pigment Decomposition—0
A Novel Approach for Intrinsic Dimension Estimation—0
Comprehensive OOD Detection Improvements—0
A comprehensive survey on computational learning methods for analysis of gene expression data—0
Compressed Dictionary Learning—0
Compressed Subspace Learning Based on Canonical Angle Preserving Property—0
Clustering based on Mixtures of Sparse Gaussian Processes—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