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
Asteroids co-orbital motion classification based on Machine Learning—0
Metastatic Breast Cancer Prognostication Through Multimodal Integration of Dimensionality Reduction Algorithms and Classification Algorithms—0
Interactive Distillation of Large Single-Topic Corpora of Scientific Papers—0
Noise-Augmented Boruta: The Neural Network Perturbation Infusion with Boruta Feature Selection—0
On the Use of the Kantorovich-Rubinstein Distance for Dimensionality Reduction—0
Detecting covariate drift in text data using document embeddings and dimensionality reductionCode0
Bridging Dense and Sparse Maximum Inner Product Search—0
Supervised Stochastic Neighbor Embedding Using Contrastive LearningCode0
Massively-Parallel Heat Map Sorting and Applications To Explainable Clustering—0
Directed Scattering for Knowledge Graph-based Cellular Signaling Analysis—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