SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 551–560 of 3304 papers

TitleStatusHype
Understanding Clinical Decision-Making in Traditional East Asian Medicine through Dimensionality Reduction: An Empirical Investigation—0
Sparse Modelling for Feature Learning in High Dimensional Data—0
Wireless Environment Information Sensing, Feature, Semantic, and Knowledge: Four Steps Towards 6G AI-Enabled Air Interface—0
Factors in Fashion: Factor Analysis towards the Mode—0
TemporalPaD: a reinforcement-learning framework for temporal feature representation and dimension reduction—0
Implementing NLPs in industrial process modeling: Addressing Categorical Variables—0
Broadcast Product: Shape-aligned Element-wise Multiplication and Beyond—0
Grading and Anomaly Detection for Automated Retinal Image Analysis using Deep Learning—0
Exploring Semantic Clustering in Deep Reinforcement Learning for Video Games—0
A parametric framework for kernel-based dynamic mode decomposition using deep learningCode0
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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