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 941–950 of 3304 papers

TitleStatusHype
Dimensionality Reduction via Diffusion Map Improved with Supervised Linear Projection—0
Dimensionality reduction via path integration for computing mRNA distributions—0
Dimensionality Reduction via Regression in Hyperspectral Imagery—0
Dimensionality reduction with missing values imputation—0
Dimensionality reduction with subgaussian matrices: a unified theory—0
Dimensionality Reduction with Subspace Structure Preservation—0
Classification Methods Based on Machine Learning for the Analysis of Fetal Health Data—0
Dimension Estimation Using Random Connection Models—0
AVIDA: Alternating method for Visualizing and Integrating Data—0
An Improved Deep Learning Model for Word Embeddings Based Clustering for Large Text Datasets—0
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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