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 2681–2690 of 3304 papers

TitleStatusHype
An Improved Deep Learning Model for Word Embeddings Based Clustering for Large Text Datasets—0
An Improved CNN-based Neural Network Model for Fruit Sugar Level Detection—0
An Improvement of PAA on Trend-Based Approximation for Time Series—0
An Incremental Dimensionality Reduction Method for Visualizing Streaming Multidimensional Data—0
An Incremental Non-Linear Manifold Approximation Method—0
An information-geometric approach to feature extraction and moment reconstruction in dynamical systems—0
An Information Theoretic Feature Selection Framework for Big Data under Apache Spark—0
Non-linear Canonical Correlation Analysis: A Compressed Representation Approach—0
An Innovative Imputation and Classification Approach for Accurate Disease Prediction—0
An interpretable multiple kernel learning approach for the discovery of integrative cancer subtypes—0
Show:102550
← PrevPage 269 of 331Next →
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