SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 921–930 of 3304 papers

TitleStatusHype
The G-invariant graph Laplacian—0
IMU-based Modularized Wearable Device for Human Motion Classification—0
Multimodal and multicontrast image fusion via deep generative models—0
Dimensionality Collapse: Optimal Measurement Selection for Low-Error Infinite-Horizon ForecastingCode0
Interpretable Linear Dimensionality Reduction based on Bias-Variance Analysis—0
Deep Linear Discriminant Analysis with Variation for Polycystic Ovary Syndrome Classification—0
Feature Space Sketching for Logistic Regression—0
Clustering based on Mixtures of Sparse Gaussian Processes—0
Data Augmentation For Label Enhancement—0
A Radiomics-Incorporated Deep Ensemble Learning Model for Multi-Parametric MRI-based Glioma Segmentation—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