scholarly journals Random subspace and random projection nearest neighbor ensembles for high dimensional data

2021 ◽  
pp. 116078
Author(s):  
Sampath Deegalla ◽  
Keerthi Walgama ◽  
Panagiotis Papapetrou ◽  
Henrik Boström
Keyword(s):  
Nearest Neighbor ◽  
High Dimensional Data ◽  
Random Projection ◽  
High Dimensional ◽  
Random Subspace

scholarly journals Random projections and Hotelling’s T2 statistics for change detection in high-dimensional data streams

2013 ◽  
Vol 23 (2) ◽  
pp. 447-461 ◽  
Author(s):  
Ewa Skubalska-Rafajłowicz
Keyword(s):  
Discrete Time ◽  
Data Streams ◽  
Random Projection ◽  
Image Sequences ◽  
High Dimensional ◽  
Random Projections ◽  
Random Subspace ◽  
Noisy Image ◽  
Method Of Dimensionality Reduction ◽  
Diagnostic Properties

The method of change (or anomaly) detection in high-dimensional discrete-time processes using a multivariate Hotelling chart is presented. We use normal random projections as a method of dimensionality reduction. We indicate diagnostic properties of the Hotelling control chart applied to data projected onto a random subspace of Rn. We examine the random projection method using artificial noisy image sequences as examples.

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