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 3226–3250 of 3304 papers

TitleStatusHype
Does a Hybrid Neural Network based Feature Selection Model Improve Text Classification?—0
Domain Adaptation for Authorship Attribution: Improved Structural Correspondence Learning—0
Domain-Dependent Speaker Diarization for the Third DIHARD Challenge—0
Domain Generalization via Domain-based Covariance Minimization—0
Don't count, predict! A systematic comparison of context-counting vs. context-predicting semantic vectors—0
Dopamine Transporter SPECT Image Classification for Neurodegenerative Parkinsonism via Diffusion Maps and Machine Learning Classifiers—0
Doubly Non-Central Beta Matrix Factorization for Stable Dimensionality Reduction of Bounded Support Matrix Data—0
Down-Sampling coupled to Elastic Kernel Machines for Efficient Recognition of Isolated Gestures—0
DPCA: Dimensionality Reduction for Discriminative Analytics of Multiple Large-Scale Datasets—0
DPDR: A novel machine learning method for the Decision Process for Dimensionality Reduction—0
Drone Flocking Optimization using NSGA-II and Principal Component Analysis—0
Dual-band feature selection for maturity classification of specialty crops by hyperspectral imaging—0
DumbleDR: Predicting User Preferences of Dimensionality Reduction Projection Quality—0
Dynamical Component Analysis (DyCA): Dimensionality Reduction For High-Dimensional Deterministic Time-Series—0
Dynamical Mode Recognition of Coupled Flame Oscillators by Supervised and Unsupervised Learning Approaches—0
Dynamical Mode Recognition of Turbulent Flames in a Swirl-stabilized Annular Combustor by a Time-series Learning Approach—0
Dynamic and Memory-efficient Shape Based Methodologies for User Type Identification in Smart Grid Applications—0
Dynamic Security Region of Natural Gas Systems in Integrated Electricity-Gas Systems—0
Dynamic Sparse Graph for Efficient Deep Learning—0
Dynamic Tensor Clustering—0
DysLexML: Screening Tool for Dyslexia Using Machine Learning—0
Early and Late Combinations of Criteria for Reranking Distributional Thesauri—0
Early detection of diabetes through transfer learning-based eye (vision) screening and improvement of machine learning model performance and advanced parameter setting algorithms—0
EasiCS: the objective and fine-grained classification method of cervical spondylosis dysfunction—0
Economic Forecasts Using Many Noises—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