Package org.pepstock.charba.client.ml

Class LinearRegression

java.lang.Object

org.pepstock.charba.client.ml.LinearRegression

All Implemented Interfaces:

IsRegression

public final class LinearRegression
extends Object

Simple Linear Regression is a type of Regression algorithms that models the relationship between a dependent variable and a single independent variable.
The relationship shown by a Simple Linear Regression model is linear or a sloped straight line, hence it is called Simple Linear Regression.
The key point in Simple Linear Regression is that the dependent variable must be a continuous/real value.
However, the independent variable can be measured on continuous or categorical values.
The Simple Linear Regression model can be represented using the below equation:

y = a₀ + a₁x

where

• a₀ is the intercept of the Regression line (can be obtained putting x=0)
• a₁ is the slope of the regression line, which tells whether the line is increasing or decreasing

Author:

Andrea "Stock" Stocchero

Field Summary

Fields

Modifier and Type	Field	Description
static int	DEFAULT_FORMULA_PRECISION	Default precision to get the formula, 2.

Method Summary

Modifier and Type	Method	Description
double	computeX(double y)	Returns a calculated X value by the Y value.
double	computeX(DataPoint dataPoint)	Returns a calculated X value by the Y value.
double	computeX(FloatingData y)	Returns a calculated X value by the Y value.
Date	computeX(TimeSeriesItem item)	Returns a calculated X value by the Y value.
Date	computeXToDate(double y)	Returns a calculated X value by the Y value.
Date	computeXToDate(DataPoint dataPoint)	Returns a calculated X value by the Y value.
Date	computeXToDate(FloatingData y)	Returns a calculated X value by the Y value.
List<Double>	getCoefficients()	Returns all calculated coefficients as a list.
RegressionDescriptor	getDescriptor()	Returns the regression descriptor.
double	getIntercept()	Returns the intercept coefficient.
double	getSlope()	Returns the slope coefficient.
RegressionType	getType()	Returns the regression type.
boolean	isConsistent()	Returns true if the regression is consistent and usable.
double	predict(double x)	Returns the Y value, calculated by the regression formula at specific X value.
List<Double>	predict(double... xValues)	Returns a list of Y values, calculated by the regression formula for specific X values.
double	predict(Date x)	Returns the Y value, calculated by the regression formula at specific X value.
List<Double>	predict(List<Double> xValues)	Returns a list of Y values, calculated by the regression formula for specific X values.
double	predict(DataPoint dataPoint)	Returns the Y value, calculated by the regression formula at specific X value.
double	predict(TimeSeriesItem item)	Returns the Y value, calculated by the regression formula at specific X value.
List<Double>	predictByDataPoints(List<DataPoint> dataPoints)	Returns a list of Y values, calculated by the regression formula for specific X values.
List<Double>	predictByDataPoints(DataPoint... dataPoints)	Returns a list of Y values, calculated by the regression formula for specific X values.
List<Double>	predictByDates(Date... xValues)	Returns a list of Y values, calculated by the regression formula for specific X values.
List<Double>	predictByDates(List<Date> xValues)	Returns a list of Y values, calculated by the regression formula for specific X values.
List<Double>	predictByTimeSeriesItems(List<TimeSeriesItem> items)	Returns a list of Y values, calculated by the regression formula for specific X values.
List<Double>	predictByTimeSeriesItems(TimeSeriesItem... items)	Returns a list of Y values, calculated by the regression formula for specific X values.
RegressionScore	score(List<Double> y)	Evaluates the regression formula if the model fits enough. X values are creating starting from 0 with increment of 1.
RegressionScore	score(List<Double> y, double starting)	Evaluates the regression formula if the model fits enough. X values are creating starting from passed argument with increment of 1.
RegressionScore	score(List<Double> y, double starting, double increment)	Evaluates the regression formula if the model fits enough. X values are creating starting from passed argument with increment of passed argument.
RegressionScore	score(List<Double> x, List<Double> y)	Evaluates the regression formula if the model fits enough.
RegressionScore	scoreByDataPoints(List<DataPoint> dataPoints)	Evaluates the regression formula if the model fits enough.
RegressionScore	scoreByDate(List<Date> x, List<Double> y)	Evaluates the regression formula if the model fits enough.
RegressionScore	scoreByTimeSeriesItems(List<TimeSeriesItem> items)	Evaluates the regression formula if the model fits enough.
String	toFormula()	Returns the formula of the regression.
String	toFormula(int precision)	Returns the formula of the regression, using the requested precision.
String	toLaTeX()	Returns the formula of the regression.
String	toLaTeX(int precision)	Returns the formula of the regression, using the requested precision.

Methods inherited from class java.lang.Object

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

Field Detail

DEFAULT_FORMULA_PRECISION

public static final int DEFAULT_FORMULA_PRECISION

Default precision to get the formula, 2.

See Also:

Constant Field Values

Method Detail

getSlope

public final double getSlope()

Returns the slope coefficient.

Returns:

the slope coefficient

getIntercept

public final double getIntercept()

Returns the intercept coefficient.

Returns:

the intercept coefficient

getCoefficients

public final List<Double> getCoefficients()

Returns all calculated coefficients as a list.

Returns:

all calculated coefficients as a list

computeX

public final double computeX(double y)

Returns a calculated X value by the Y value.

Parameters:

y - Y value to use to calculate the X value

Returns:

a calculated X value by the Y value

computeX

public final double computeX(FloatingData y)

Returns a calculated X value by the Y value.

Parameters:

y - Y value to use to calculate the X value

Returns:

a calculated X value by the Y value

computeX

public final double computeX(DataPoint dataPoint)

Returns a calculated X value by the Y value.

Parameters:

dataPoint - Y value to use to calculate the X value

Returns:

a calculated X value by the Y value

computeX

public final Date computeX(TimeSeriesItem item)

Returns a calculated X value by the Y value.

Parameters:

item - Y value to use to calculate the X value

Returns:

a calculated X value by the Y value

computeXToDate

public final Date computeXToDate(double y)

Returns a calculated X value by the Y value.

Parameters:

y - Y value to use to calculate the X value

Returns:

a calculated X value by the Y value

computeXToDate

public final Date computeXToDate(FloatingData y)

Returns a calculated X value by the Y value.

Parameters:

y - Y value to use to calculate the X value

Returns:

a calculated X value by the Y value

computeXToDate

public final Date computeXToDate(DataPoint dataPoint)

Returns a calculated X value by the Y value.

Parameters:

dataPoint - Y value to use to calculate the X value

Returns:

a calculated X value by the Y value

getType

public final RegressionType getType()

Returns the regression type.

Specified by:

getType in interface IsRegression

Returns:

the regression type

getDescriptor

public final RegressionDescriptor getDescriptor()

Returns the regression descriptor.

Specified by:

getDescriptor in interface IsRegression

Returns:

the regression descriptor

isConsistent

public final boolean isConsistent()

Description copied from interface: IsRegression

Returns true if the regression is consistent and usable.

Specified by:

isConsistent in interface IsRegression

Returns:

true if the regression is consistent and usable

predict

public final double predict(double x)

Description copied from interface: IsRegression

Returns the Y value, calculated by the regression formula at specific X value.

Specified by:

predict in interface IsRegression

Parameters:

x - value to use to get the predicted value

Returns:

the Y value, calculated by the regression formula at specific X value

predict

public final double predict(Date x)

Description copied from interface: IsRegression

Returns the Y value, calculated by the regression formula at specific X value.

Specified by:

predict in interface IsRegression

Parameters:

x - value to use to get the predicted value

Returns:

the Y value, calculated by the regression formula at specific X value

predict

public final double predict(DataPoint dataPoint)

Description copied from interface: IsRegression

Returns the Y value, calculated by the regression formula at specific X value.

Specified by:

predict in interface IsRegression

Parameters:

dataPoint - value to use to get the predicted value

Returns:

the Y value, calculated by the regression formula at specific X value

predict

public final double predict(TimeSeriesItem item)

Description copied from interface: IsRegression

Returns the Y value, calculated by the regression formula at specific X value.

Specified by:

predict in interface IsRegression

Parameters:

item - value to use to get the predicted value

Returns:

the Y value, calculated by the regression formula at specific X value

predict

public final List<Double> predict(double... xValues)

Description copied from interface: IsRegression

Returns a list of Y values, calculated by the regression formula for specific X values.

Specified by:

predict in interface IsRegression

Parameters:

xValues - values to use to get the predicted values

Returns:

a list of Y values, calculated by the regression formula for specific X values

predict

public final List<Double> predict(List<Double> xValues)

Description copied from interface: IsRegression

Returns a list of Y values, calculated by the regression formula for specific X values.

Specified by:

predict in interface IsRegression

Parameters:

xValues - values to use to get the predicted values

Returns:

a list of Y values, calculated by the regression formula for specific X values

predictByDates

public final List<Double> predictByDates(Date... xValues)

Description copied from interface: IsRegression

Returns a list of Y values, calculated by the regression formula for specific X values.

Specified by:

predictByDates in interface IsRegression

Parameters:

xValues - values to use to get the predicted values

Returns:

a list of Y values, calculated by the regression formula for specific X values

predictByDates

public final List<Double> predictByDates(List<Date> xValues)

Description copied from interface: IsRegression

Returns a list of Y values, calculated by the regression formula for specific X values.

Specified by:

predictByDates in interface IsRegression

Parameters:

xValues - values to use to get the predicted values

Returns:

a list of Y values, calculated by the regression formula for specific X values

predictByDataPoints

public final List<Double> predictByDataPoints(DataPoint... dataPoints)

Description copied from interface: IsRegression

Returns a list of Y values, calculated by the regression formula for specific X values.

Specified by:

predictByDataPoints in interface IsRegression

Parameters:

dataPoints - values to use to get the predicted values

Returns:

a list of Y values, calculated by the regression formula for specific X values

predictByDataPoints

public final List<Double> predictByDataPoints(List<DataPoint> dataPoints)

Description copied from interface: IsRegression

Returns a list of Y values, calculated by the regression formula for specific X values.

Specified by:

predictByDataPoints in interface IsRegression

Parameters:

dataPoints - values to use to get the predicted values

Returns:

a list of Y values, calculated by the regression formula for specific X values

predictByTimeSeriesItems

public final List<Double> predictByTimeSeriesItems(TimeSeriesItem... items)

Description copied from interface: IsRegression

Returns a list of Y values, calculated by the regression formula for specific X values.

Specified by:

predictByTimeSeriesItems in interface IsRegression

Parameters:

items - values to use to get the predicted values

Returns:

a list of Y values, calculated by the regression formula for specific X values

predictByTimeSeriesItems

public final List<Double> predictByTimeSeriesItems(List<TimeSeriesItem> items)

Description copied from interface: IsRegression

Returns a list of Y values, calculated by the regression formula for specific X values.

Specified by:

predictByTimeSeriesItems in interface IsRegression

Parameters:

items - values to use to get the predicted values

Returns:

a list of Y values, calculated by the regression formula for specific X values

score

public final RegressionScore score(List<Double> y)

Description copied from interface: IsRegression

Evaluates the regression formula if the model fits enough.
X values are creating starting from 0 with increment of 1.

Specified by:

score in interface IsRegression

Parameters:

y - Y values to use for evaluation

Returns:

the score of the regression

score

public final RegressionScore score(List<Double> y,
                                   double starting)

Description copied from interface: IsRegression

Evaluates the regression formula if the model fits enough.
X values are creating starting from passed argument with increment of 1.

Specified by:

score in interface IsRegression

Parameters:

y - Y values to use for evaluation

starting - starting value to create X values

Returns:

the score of the regression

score

public final RegressionScore score(List<Double> y,
                                   double starting,
                                   double increment)

Description copied from interface: IsRegression

Evaluates the regression formula if the model fits enough.
X values are creating starting from passed argument with increment of passed argument.

Specified by:

score in interface IsRegression

Parameters:

y - Y values to use for evaluation

starting - starting value to create X values

increment - increment to apply to the starting value

Returns:

the score of the regression

score

public final RegressionScore score(List<Double> x,
                                   List<Double> y)

Description copied from interface: IsRegression

Evaluates the regression formula if the model fits enough.

Specified by:

score in interface IsRegression

Parameters:

x - X values to use for evaluation

y - Y values to use for evaluation

Returns:

the score of the regression

scoreByDate

public final RegressionScore scoreByDate(List<Date> x,
                                         List<Double> y)

Description copied from interface: IsRegression

Evaluates the regression formula if the model fits enough.

Specified by:

scoreByDate in interface IsRegression

Parameters:

x - X values to use for evaluation

y - Y values to use for evaluation

Returns:

the score of the regression

scoreByDataPoints

public final RegressionScore scoreByDataPoints(List<DataPoint> dataPoints)

Description copied from interface: IsRegression

Evaluates the regression formula if the model fits enough.

Specified by:

scoreByDataPoints in interface IsRegression

Parameters:

dataPoints - X and Y values to use for evaluation

Returns:

the score of the regression

scoreByTimeSeriesItems

public final RegressionScore scoreByTimeSeriesItems(List<TimeSeriesItem> items)

Description copied from interface: IsRegression

Evaluates the regression formula if the model fits enough.

Specified by:

scoreByTimeSeriesItems in interface IsRegression

Parameters:

items - X and Y values to use for evaluation

Returns:

the score of the regression

toFormula

public final String toFormula()

Description copied from interface: IsRegression

Returns the formula of the regression.

Specified by:

toFormula in interface IsRegression

Returns:

the formula of the regression

toFormula

public final String toFormula(int precision)

Description copied from interface: IsRegression

Returns the formula of the regression, using the requested precision.

Specified by:

toFormula in interface IsRegression

Parameters:

precision - precision to apply to the numbers of the formula

Returns:

the formula of the regression

toLaTeX

public final String toLaTeX()

Description copied from interface: IsRegression

Returns the formula of the regression.

Specified by:

toLaTeX in interface IsRegression

Returns:

the formula of the regression

toLaTeX

public final String toLaTeX(int precision)

Description copied from interface: IsRegression

Returns the formula of the regression, using the requested precision.

Specified by:

toLaTeX in interface IsRegression

Parameters:

precision - precision to apply to the numbers of the formula

Returns:

the formula of the regression