Weight by PCA
This operator uses the factors of a PCA component (usually the first) as feature weights.
Uses the factors of one of the principal components (default is the first) as feature weights. Please note that the PCA weighting operator is currently the only one which also works on data sets without a label, i.e. for unsupervised learning.
- example set: expects: ExampleSet
- example set:
- normalize weights:
Activates the normalization of all weights.
Range: boolean; default: true
- component number:
Indicates the number of the component from which the weights should be calculated.
Range: integer; 1-+?; default: 1