javax.visrec.ml.regression

Class SimpleLinearRegression<MODEL_CLASS>

java.lang.Object

javax.visrec.ml.regression.SimpleLinearRegression<MODEL_CLASS>

All Implemented Interfaces:

Regressor<Float,Float>, ModelProvider<MODEL_CLASS>

public abstract class SimpleLinearRegression<MODEL_CLASS>
extends Object
implements Regressor<Float,Float>, ModelProvider<MODEL_CLASS>

Simple linear regression finds the best possible straight line that tries to explain given training set.

Author:

zoran

Constructor Summary

Constructors

Constructor and Description
SimpleLinearRegression()

Method Summary

Modifier and Type	Method and Description
abstract float	getIntercept() The value of output when input is zero
MODEL_CLASS	getModel()
abstract float	getSlope() How much on average output change when input changes by one.
abstract Float	predict(Float inputs)
protected void	setModel(MODEL_CLASS model)

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

SimpleLinearRegression

public SimpleLinearRegression()

Method Detail

getModel

public MODEL_CLASS getModel()

Specified by:

getModel in interface ModelProvider<MODEL_CLASS>

setModel

protected void setModel(MODEL_CLASS model)

predict

public abstract Float predict(Float inputs)

Specified by:

predict in interface Regressor<Float,Float>

getSlope

public abstract float getSlope()

How much on average output change when input changes by one. If it is zero there is no linear dependency between input and output, and data is probably scattered. If it is less then one output grows slower then input. If it is greater than one, then output is growing faster than input. If its negative, then output is lowering as input grows.

Returns:

getIntercept

public abstract float getIntercept()

The value of output when input is zero

Returns: