Statements (30)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
statistical analysis
|
| gptkbp:assumes |
large variance is informative
linear relationships |
| gptkbp:category |
data analysis
pattern recognition multivariate statistics |
| gptkbp:fullName |
Principal Component Analysis
|
| https://www.w3.org/2000/01/rdf-schema#label |
PCA
|
| 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:church
|
| gptkbp:bfsLayer |
4
|