EigenPairFilter (ELKI: Environment for DeveLoping KDD-Applications Supported by Index-Structures)

All Known Implementing Classes:

DropEigenPairFilter, FirstNEigenPairFilter, LimitEigenPairFilter, PercentageEigenPairFilter, ProgressiveEigenPairFilter, RelativeEigenPairFilter, SignificantEigenPairFilter, WeakEigenPairFilter
```
public interface EigenPairFilter
```
The eigenpair filter is used to filter eigenpairs (i.e. eigenvectors and their corresponding eigenvalues) which are a result of a Variance Analysis Algorithm, e.g., Principal Component Analysis. The eigenpairs are filtered into two types: strong and weak eigenpairs, where strong eigenpairs having high variances and weak eigenpairs having small variances.

Since:

0.1

Author:

Elke Achtert

Field Summary

Fields
Modifier and Type	Field	Description
`static OptionID`	`PCA_EIGENPAIR_FILTER`	Parameter to specify the filter for determination of the strong and weak eigenvectors, must be a subclass of `EigenPairFilter`.

Method Summary

All Methods Instance Methods Abstract Methods
Modifier and Type	Method	Description
`int`	`filter(double[] eigenValues)`	Filters the specified eigenvalues into strong and weak eigenvalues, where strong eigenvalues have high variance and weak eigenvalues have small variance.

- Field Detail
  - PCA_EIGENPAIR_FILTER
```
static final OptionID PCA_EIGENPAIR_FILTER
```
    Parameter to specify the filter for determination of the strong and weak eigenvectors, must be a subclass of EigenPairFilter.
- Method Detail
  - filter
```
int filter(double[] eigenValues)
```
    Filters the specified eigenvalues into strong and weak eigenvalues, where strong eigenvalues have high variance and weak eigenvalues have small variance.
    
    Parameters:
    
    eigenValues - the array of eigenvalues, must be sorted descending
    
    Returns:
    
    the number of eigenvectors to keep