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gptkbp:instanceOf
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gptkb:statistical_analysis
|
|
gptkbp:assumes
|
large variance is informative
linear relationships
|
|
gptkbp:category
|
data analysis
pattern recognition
multivariate statistics
|
|
gptkbp:fullName
|
Principal Component Analysis
|
|
gptkbp:input
|
numerical data
|
|
gptkbp:introduced
|
gptkb:Karl_Pearson
|
|
gptkbp:introducedIn
|
1901
|
|
gptkbp:limitation
|
assumes orthogonality of components
sensitive to scaling
not suitable for categorical data
|
|
gptkbp:output
|
principal components
|
|
gptkbp:relatedTo
|
gptkb:Eigenvalue_decomposition
gptkb:Singular_Value_Decomposition
|
|
gptkbp:step
|
center data
compute covariance matrix
compute eigenvectors and eigenvalues
project data onto principal components
|
|
gptkbp:supportsAlgorithm
|
unsupervised learning
|
|
gptkbp:usedFor
|
gptkb:data_visualization
dimensionality reduction
feature extraction
|
|
gptkbp:usedIn
|
gptkb:machine_learning
gptkb:signal_processing
statistics
|
|
gptkbp:bfsParent
|
gptkb:principal_component_analysis
gptkb:Permanent_Court_of_Arbitration
gptkb:Presbyterian_Church_in_America
|
|
gptkbp:bfsLayer
|
5
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
PCA
|