SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 881–890 of 3304 papers

TitleStatusHype
Diffusion State Distances: Multitemporal Analysis, Fast Algorithms, and Applications to Biological Networks—0
Digital Fingerprinting of Microstructures—0
An Improved Deep Learning Model for Word Embeddings Based Clustering for Large Text Datasets—0
DimenFix: A novel meta-dimensionality reduction method for feature preservation—0
Dimensionality-reduced subspace clustering—0
Dimensionality Reduction and Anomaly Detection for CPPS Data using Autoencoder—0
A Unified Framework for Optimization-Based Graph Coarsening—0
Dimensionality Reduction and Classification feature using Mutual Information applied to Hyperspectral Images : A Filter strategy based algorithm—0
Classification at the Accuracy Limit -- Facing the Problem of Data Ambiguity—0
Classic machine learning methods—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