E nvironment for Deve L oping K DD-Applications Supported by I ndex-Structures

## de.lmu.ifi.dbs.elki.data.model Class CorrelationAnalysisSolution<V extends NumberVector<V,?>>

```java.lang.Object
de.lmu.ifi.dbs.elki.data.model.CorrelationAnalysisSolution<V>
```
Type Parameters:
`V` - the type of NumberVector handled by this Result
All Implemented Interfaces:
Model, Result, TextWriteable

`public class CorrelationAnalysisSolution<V extends NumberVector<V,?>>extends Objectimplements TextWriteable, Result, Model`

A solution of correlation analysis is a matrix of equations describing the dependencies.

Author:
Arthur Zimek

Field Summary
`private  Vector` `centroid`
The centroid if the objects belonging to the hyperplane induced by the correlation.
`private  int` `correlationDimensionality`
The dimensionality of the correlation.
`private  LinearEquationSystem` `linearEquationSystem`
Stores the solution equations.
`private  NumberFormat` `nf`
Number format for output accuracy.
`private  Matrix` `similarityMatrix`
The similarity matrix of the pca.
`private  double` `standardDeviation`
The standard deviation within this solution.
`private  Matrix` `strongEigenvectors`
The strong eigenvectors of the hyperplane induced by the correlation.
`private  Matrix` `weakEigenvectors`
The weak eigenvectors of the hyperplane induced by the correlation.

Constructor Summary
```CorrelationAnalysisSolution(LinearEquationSystem solution, Database<V> db, Matrix strongEigenvectors, Matrix weakEigenvectors, Matrix similarityMatrix, Vector centroid)```
Provides a new CorrelationAnalysisSolution holding the specified matrix.
```CorrelationAnalysisSolution(LinearEquationSystem solution, Database<V> db, Matrix strongEigenvectors, Matrix weakEigenvectors, Matrix similarityMatrix, Vector centroid, NumberFormat nf)```
Provides a new CorrelationAnalysisSolution holding the specified matrix and number format.

Method Summary
` Matrix` `dataProjections(V p)`
Returns the data vectors after projection.
` Vector` `dataVector(V p)`
Returns the data vectors after projection.
` Matrix` `dataVectors(Matrix p)`
Returns the data vectors after projection.
`private  double` `distance(Matrix p)`
Returns the distance of Matrix p from the hyperplane underlying this solution.
` double` `distance(V p)`
Returns the distance of NumberVector p from the hyperplane underlying this solution.
` Vector` `errorVector(V p)`
Returns the error vectors after projection.
` Matrix` `errorVectors(Matrix p)`
Returns the error vectors after projection.
` Matrix` `errorVectors(V p)`
Returns the error vectors after projection.
` Vector` `getCentroid()`
Returns the centroid of this model.
` int` `getCorrelationDimensionality()`
Return the correlation dimensionality.
` String` `getName()`
Get a user-understandable name for this result.
` LinearEquationSystem` `getNormalizedLinearEquationSystem(Normalization<V> normalization)`
Returns the linear equation system for printing purposes.
` Matrix` `getSimilarityMatrix()`
Returns the similarity matrix of the pca.
` double` `getStandardDeviation()`
Returns the standard deviation of the distances of the objects belonging to the hyperplane underlying this solution.
` Matrix` `getStrongEigenvectors()`
Returns a copy of the strong eigenvectors.
` Matrix` `getWeakEigenvectors()`
Returns a copy of the weak eigenvectors.
` void` ```writeToText(TextWriterStream out, String label)```
Text output of the equation system

Methods inherited from class java.lang.Object
`clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Field Detail

### linearEquationSystem

`private LinearEquationSystem linearEquationSystem`
Stores the solution equations.

### nf

`private NumberFormat nf`
Number format for output accuracy.

### correlationDimensionality

`private int correlationDimensionality`
The dimensionality of the correlation.

### standardDeviation

`private final double standardDeviation`
The standard deviation within this solution.

### weakEigenvectors

`private final Matrix weakEigenvectors`
The weak eigenvectors of the hyperplane induced by the correlation.

### strongEigenvectors

`private final Matrix strongEigenvectors`
The strong eigenvectors of the hyperplane induced by the correlation.

### similarityMatrix

`private final Matrix similarityMatrix`
The similarity matrix of the pca.

### centroid

`private final Vector centroid`
The centroid if the objects belonging to the hyperplane induced by the correlation.

Constructor Detail

### CorrelationAnalysisSolution

```public CorrelationAnalysisSolution(LinearEquationSystem solution,
Database<V> db,
Matrix strongEigenvectors,
Matrix weakEigenvectors,
Matrix similarityMatrix,
Vector centroid)```
Provides a new CorrelationAnalysisSolution holding the specified matrix.

Parameters:
`solution` - the linear equation system describing the solution equations
`db` - the database containing the objects
`strongEigenvectors` - the strong eigenvectors of the hyperplane induced by the correlation
`weakEigenvectors` - the weak eigenvectors of the hyperplane induced by the correlation
`similarityMatrix` - the similarity matrix of the underlying distance computations
`centroid` - the centroid if the objects belonging to the hyperplane induced by the correlation

### CorrelationAnalysisSolution

```public CorrelationAnalysisSolution(LinearEquationSystem solution,
Database<V> db,
Matrix strongEigenvectors,
Matrix weakEigenvectors,
Matrix similarityMatrix,
Vector centroid,
NumberFormat nf)```
Provides a new CorrelationAnalysisSolution holding the specified matrix and number format.

Parameters:
`solution` - the linear equation system describing the solution equations
`db` - the database containing the objects
`strongEigenvectors` - the strong eigenvectors of the hyperplane induced by the correlation
`weakEigenvectors` - the weak eigenvectors of the hyperplane induced by the correlation
`similarityMatrix` - the similarity matrix of the underlying distance computations
`centroid` - the centroid if the objects belonging to the hyperplane induced by the correlation
`nf` - the number format for output accuracy
Method Detail

### getNormalizedLinearEquationSystem

```public LinearEquationSystem getNormalizedLinearEquationSystem(Normalization<V> normalization)
throws NonNumericFeaturesException```
Returns the linear equation system for printing purposes. If normalization is null the linear equation system is returned, otherwise the linear equation system will be transformed according to the normalization.

Parameters:
`normalization` - the normalization, can be null
Returns:
the linear equation system for printing purposes
Throws:
`NonNumericFeaturesException` - if the linear equation system is not compatible with values initialized during normalization

### getCorrelationDimensionality

`public int getCorrelationDimensionality()`
Return the correlation dimensionality.

Returns:
the correlation dimensionality

### distance

`public double distance(V p)`
Returns the distance of NumberVector p from the hyperplane underlying this solution.

Parameters:
`p` - a vector in the space underlying this solution
Returns:
the distance of p from the hyperplane underlying this solution

### distance

`private double distance(Matrix p)`
Returns the distance of Matrix p from the hyperplane underlying this solution.

Parameters:
`p` - a vector in the space underlying this solution
Returns:
the distance of p from the hyperplane underlying this solution

### errorVectors

`public Matrix errorVectors(V p)`
Returns the error vectors after projection.

Parameters:
`p` - a vector in the space underlying this solution
Returns:
the error vectors

### errorVectors

`public Matrix errorVectors(Matrix p)`
Returns the error vectors after projection.

Parameters:
`p` - a vector in the space underlying this solution
Returns:
the error vectors

### errorVector

`public Vector errorVector(V p)`
Returns the error vectors after projection.

Parameters:
`p` - a vector in the space underlying this solution
Returns:
the error vectors

### dataProjections

`public Matrix dataProjections(V p)`
Returns the data vectors after projection.

Parameters:
`p` - a vector in the space underlying this solution
Returns:
the data projections

### dataVectors

`public Matrix dataVectors(Matrix p)`
Returns the data vectors after projection.

Parameters:
`p` - a vector in the space underlying this solution
Returns:
the error vectors

### dataVector

`public Vector dataVector(V p)`
Returns the data vectors after projection.

Parameters:
`p` - a vector in the space underlying this solution
Returns:
the error vectors

### getStandardDeviation

`public double getStandardDeviation()`
Returns the standard deviation of the distances of the objects belonging to the hyperplane underlying this solution.

Returns:
the standard deviation of this solution

### getStrongEigenvectors

`public Matrix getStrongEigenvectors()`
Returns a copy of the strong eigenvectors.

Returns:
a copy of the strong eigenvectors

### getWeakEigenvectors

`public Matrix getWeakEigenvectors()`
Returns a copy of the weak eigenvectors.

Returns:
a copy of the weak eigenvectors

### getSimilarityMatrix

`public Matrix getSimilarityMatrix()`
Returns the similarity matrix of the pca.

Returns:
the similarity matrix of the pca

### getCentroid

`public Vector getCentroid()`
Returns the centroid of this model.

Returns:
the centroid of this model

### writeToText

```public void writeToText(TextWriterStream out,
String label)```
Text output of the equation system

Specified by:
`writeToText` in interface `TextWriteable`
Parameters:
`out` - Output writer
`label` - Label

### getName

`public String getName()`
Description copied from interface: `Result`
Get a user-understandable name for this result. Defaults may be returned such as "list" for a list result.

Specified by:
`getName` in interface `Result`
Returns:
result name

 Release 0.3 (2010-03-31_1612)