SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 401–410 of 3304 papers

TitleStatusHype
Accelerated partial separable model using dimension-reduced optimization technique for ultra-fast cardiac MRI—0
A Light weight and Hybrid Deep Learning Model based Online Signature Verification—0
Asteroids co-orbital motion classification based on Machine Learning—0
AstroM^3: A self-supervised multimodal model for astronomy—0
A Study of Feature Selection and Extraction Algorithms for Cancer Subtype Prediction—0
A study of semantic augmentation of word embeddings for extractive summarization—0
Approximation Algorithms for Sparse Principal Component Analysis—0
The Effects of Spectral Dimensionality Reduction on Hyperspectral Pixel Classification: A Case Study—0
A Subspace-based Approach for Dimensionality Reduction and Important Variable Selection—0
A Hybrid Deep Learning CNN Model for Enhanced COVID-19 Detection from Computed Tomography (CT) Scan Images—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