## gov.sandia.cognition.learning.data.feature Class LinearRegressionCoefficientExtractor

```java.lang.Object
gov.sandia.cognition.util.AbstractCloneableSerializable
gov.sandia.cognition.evaluator.AbstractStatefulEvaluator<Vector,Vector,FiniteCapacityBuffer<Vector>>
gov.sandia.cognition.learning.data.feature.LinearRegressionCoefficientExtractor
```
All Implemented Interfaces:
Evaluator<Vector,Vector>, StatefulEvaluator<Vector,Vector,FiniteCapacityBuffer<Vector>>, CloneableSerializable, Serializable, Cloneable

```@CodeReview(reviewer="Kevin R. Dixon",
date="2006-07-17",
changesNeeded=false,
public class LinearRegressionCoefficientExtractorextends AbstractStatefulEvaluator<Vector,Vector,FiniteCapacityBuffer<Vector>>```

Takes a sampled sequence of equal-dimension vectors as input and computes the linear regression coefficients for each dimension in the vectors. In other words, it compute the best-fit equation:
y_i = m*x_i + b,
where "m" and "b" are the slope and offset for that dimension in the buffer. For each "i" vector dimension in the regression buffer. Thus, if one puts vectors of dimension "n" into the buffer, at each timestep, one will get one vector of slopes (m) and one vector of offsets (b), each of dimension n. The output of the evaluate() method is a Matrix with first column of slopes, and the next column of offsets.

Since:
1.0
Author:
Justin Basilico
Serialized Form

Field Summary
`static int` `DEFAULT_MAX_BUFFER_SIZE`
Default maximum buffer size, 20.

Constructor Summary
`LinearRegressionCoefficientExtractor()`
Default constructor.
`LinearRegressionCoefficientExtractor(int maxBufferSize)`
Creates new instance of LinearRegressionEvaluator

Method Summary
` LinearRegressionCoefficientExtractor` `clone()`
This makes public the clone method on the `Object` class and removes the exception that it throws.
` FiniteCapacityBuffer<Vector>` `createDefaultState()`
Creates a new default state object.
` Vector` `evaluate(Vector input)`
Evaluates the object using the given input and current state objects, returning the output.
` int` `getMaxBufferSize()`
Getter for maxBufferSize
` void` `setMaxBufferSize(int maxBufferSize)`
Setter for maxBufferSize

Methods inherited from class gov.sandia.cognition.evaluator.AbstractStatefulEvaluator
`evaluate, getState, resetState, setState`

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

Field Detail

### DEFAULT_MAX_BUFFER_SIZE

`public static final int DEFAULT_MAX_BUFFER_SIZE`
Default maximum buffer size, 20.

Constant Field Values
Constructor Detail

### LinearRegressionCoefficientExtractor

`public LinearRegressionCoefficientExtractor()`
Default constructor.

### LinearRegressionCoefficientExtractor

`public LinearRegressionCoefficientExtractor(int maxBufferSize)`
Creates new instance of LinearRegressionEvaluator

Parameters:
`maxBufferSize` - maximum number of vectors to hold in the buffer
Method Detail

### clone

`public LinearRegressionCoefficientExtractor clone()`
Description copied from class: `AbstractCloneableSerializable`
This makes public the clone method on the `Object` class and removes the exception that it throws. Its default behavior is to automatically create a clone of the exact type of object that the clone is called on and to copy all primitives but to keep all references, which means it is a shallow copy. Extensions of this class may want to override this method (but call `super.clone()` to implement a "smart copy". That is, to target the most common use case for creating a copy of the object. Because of the default behavior being a shallow copy, extending classes only need to handle fields that need to have a deeper copy (or those that need to be reset). Some of the methods in `ObjectUtil` may be helpful in implementing a custom clone method. Note: The contract of this method is that you must use `super.clone()` as the basis for your implementation.

Specified by:
`clone` in interface `CloneableSerializable`
Overrides:
`clone` in class `AbstractStatefulEvaluator<Vector,Vector,FiniteCapacityBuffer<Vector>>`
Returns:
A clone of this object.

### createDefaultState

`public FiniteCapacityBuffer<Vector> createDefaultState()`
Description copied from interface: `StatefulEvaluator`
Creates a new default state object.

Returns:
A new default state object.

### evaluate

`public Vector evaluate(Vector input)`
Description copied from interface: `StatefulEvaluator`
Evaluates the object using the given input and current state objects, returning the output. The current state may be modified by side effect.

Parameters:
`input` - The input to evaluate.
Returns:
output that results from the evaluation, state is modified by side effect

### getMaxBufferSize

`public int getMaxBufferSize()`
Getter for maxBufferSize

Returns:
Maximum Buffer size

### setMaxBufferSize

`public void setMaxBufferSize(int maxBufferSize)`
Setter for maxBufferSize

Parameters:
`maxBufferSize` - Maximum buffer size, must be >= 2