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Dimensionality reduction

Known as: Dimension reduction, Reduction 
In machine learning and statistics, dimensionality reduction or dimension reduction is the process of reducing the number of random variables under… 
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Related topics

Related topics

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Apache SparkAutoencoderBackpropagationBias–variance tradeoff

Broader (1)

Machine learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2015
2015
A unified multiset canonical correlation analysis framework based on graph embedding for multiple feature extraction
2012
2012
A novel neural-network approach of analog fault diagnosis based on kernel discriminant analysis and particle swarm optimization
2012
2012
Unsupervised Visual Data Mining Using Self-organizing Maps and a Data-driven Color Mapping
This paper presents a new approach for visually mining multivariate datasets and especially large ones. This unsupervised… 
2011
2011
Statistical semantics for enhancing document clustering
Document clustering algorithms usually use vector space model (VSM) as their underlying model for document representation. VSM… 
2011
2011
A simple model for laser drilling
2011
2011
Enhanced Sparse Imputation Techniques for a Robust Speech Recognition Front-End
Missing data techniques (MDTs) have been widely employed and shown to improve speech recognition results under noisy conditions… 
Highly Cited
2009
Highly Cited
2009
Extracting the optimal dimensionality for local tensor discriminant analysis
Highly Cited
2006
Highly Cited
2006
Integration of articulatory and spectrum features based on the hybrid HMM/BN modeling framework
Highly Cited
2002
Highly Cited
2002
A comparative analysis of basic pattern recognition techniques for the development of small size electronic nose
Highly Cited
1999
Highly Cited
1999
Relational discriminant analysis
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