SOTAVerified

Dimensionality Reduction

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

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Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 851–860 of 3304 papers

TitleStatusHype
Detecting the Trend in Musical Taste over the Decade -- A Novel Feature Extraction Algorithm to Classify Musical Content with Simple Features—0
Detection and Evaluation of Clusters within Sequential Data—0
Detection and Identification Accuracy of PCA-Accelerated Real-Time Processing of Hyperspectral Imagery—0
Classification Methods Based on Machine Learning for the Analysis of Fetal Health Data—0
Detection and tracking of gas plumes in LWIR hyperspectral video sequence data—0
Detection of Alzheimer's Disease Using Graph-Regularized Convolutional Neural Network Based on Structural Similarity Learning of Brain Magnetic Resonance Images—0
Novel Epileptic Seizure Detection Techniques and their Empirical Analysis—0
Detection of Epileptic Seizures on EEG Signals Using ANFIS Classifier, Autoencoders and Fuzzy Entropies—0
DG-GL: Differential geometry based geometric learning of molecular datasets—0
An Improved Deep Learning Model for Word Embeddings Based Clustering for Large Text Datasets—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