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Limitations of nonlinear PCA as performed with generic neural networks
Edward C. Malthouse
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Integrated Marketing Communications
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peer-review
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INIS
nonlinear problems
100%
layers
75%
curves
75%
principal component analysis
75%
surfaces
62%
values
25%
neural networks
25%
data
12%
geometry
12%
output
12%
errors
12%
extraction
12%
approximations
12%
pca
12%
Computer Science
Component Analysis
75%
Principal Component
75%
Training Data
12%
Simulation Mode
12%
Continuous Function
12%
Geometric Interpretation
12%
Relationships
12%
Networks
12%
Identification
12%
Approximation (Algorithm)
12%
Feature Extraction
12%
Economics, Econometrics and Finance
Principal Component Analysis
75%