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 1691–1700 of 3304 papers

TitleStatusHype
Deconfounding Scores: Feature Representations for Causal Effect Estimation with Weak Overlap—0
Adversarially-Trained Nonnegative Matrix FactorizationCode0
Granger Causality Based Hierarchical Time Series Clustering for State Estimation—0
Class-Wise Principal Component Analysis for hyperspectral image feature extraction—0
Deep Features for training Support Vector Machine—0
Predicting Inflation with Recurrent Neural Networks—0
Adapting Speaker Embeddings for Speaker Diarisation—0
Dopamine Transporter SPECT Image Classification for Neurodegenerative Parkinsonism via Diffusion Maps and Machine Learning Classifiers—0
Mitigating Gradient-based Adversarial Attacks via Denoising and Compression—0
Deep Learning of Conjugate MappingsCode0
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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