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 1731–1740 of 3304 papers

TitleStatusHype
Evaluating Explanatory Capabilities of Machine Learning Models in Medical Diagnostics: A Human-in-the-Loop Approach—0
Evaluating Feature Extraction Methods for Knowledge-based Biomedical Word Sense Disambiguation—0
Evaluating Graph Signal Processing for Neuroimaging Through Classification and Dimensionality Reduction—0
Evaluating the Stability of Deep Learning Latent Feature Spaces—0
Evaluating the Stability of Semantic Concept Representations in CNNs for Robust Explainability—0
Evaluating Unsupervised Dimensionality Reduction Methods for Pretrained Sentence Embeddings—0
Evaluation of company investment value based on machine learning—0
Evaluation of distance-based approaches for forensic comparison: Application to hand odor evidence—0
Evaluation Of Hidden Markov Models Using Deep CNN Features In Isolated Sign Recognition—0
Evaluation of PPG Biometrics for Authentication in different states—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