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 2651–2675 of 3304 papers

TitleStatusHype
An Automated Data Mining Framework Using Autoencoders for Feature Extraction and Dimensionality Reduction—0
An Efficient and Reliable Tolerance-Based Algorithm for Principal Component Analysis—0
An Efficient Feature Selection in Classification of Audio Files—0
An efficient label-free analyte detection algorithm for time-resolved spectroscopy—0
An Efficient Large-scale Semi-supervised Multi-label Classifier Capable of Handling Missing labels—0
Building an Efficient Intrusion Detection System Based on Feature Selection and Ensemble Classifier—0
An efficient real-time target tracking algorithm using adaptive feature fusion—0
An Empirical Study of Dimensional Reduction Techniques for Facial Action Units Detection—0
An Empirical Study on the Joint Impact of Feature Selection and Data Re-sampling on Imbalance Classification—0
An enhanced Teaching-Learning-Based Optimization (TLBO) with Grey Wolf Optimizer (GWO) for text feature selection and clustering—0
An Entropy Based Outlier Score and its Application to Novelty Detection for Road Infrastructure Images—0
A Neural Network for Determination of Latent Dimensionality in Nonnegative Matrix Factorization—0
A Neural Network Transformer Model for Composite Microstructure Homogenization—0
A Neural Operator-Based Emulator for Regional Shallow Water Dynamics—0
A New Approach for Scalable Analysis of Microbial Communities—0
A New Approach to Dimensionality Reduction for Anomaly Detection in Data Traffic—0
A new band selection approach based on information theory and support vector machine for hyperspectral images reduction and classification—0
A New Covariance Estimator for Sufficient Dimension Reduction in High-Dimensional and Undersized Sample Problems—0
A New Dimensionality Reduction Method Based on Hensel's Compression for Privacy Protection in Federated Learning—0
A new filter for dimensionality reduction and classification of hyperspectral images using GLCM features and mutual information—0
A new method color MS-BSIF Features learning for the robust kinship verification—0
A New Method for Performance Analysis in Nonlinear Dimensionality Reduction—0
A new parsimonious method for classifying Cancer Tissue-of-Origin Based on DNA Methylation 450K data—0
A new set of cluster driven composite development indicators—0
A New Spatio-Spectral Morphological Segmentation For Multi-Spectral Remote-Sensing Images—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