|
||||||||||
PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
java.lang.Objectweka.classifiers.Classifier
weka.classifiers.functions.LinearRegression
public class LinearRegression
Class for using linear regression for prediction. Uses the Akaike criterion for model selection, and is able to deal with weighted instances.
Valid options are:-D Produce debugging output. (default no debugging output)
-S <number of selection method> Set the attribute selection method to use. 1 = None, 2 = Greedy. (default 0 = M5' method)
-C Do not try to eliminate colinear attributes.
-R <double> Set ridge parameter (default 1.0e-8).
Field Summary | |
---|---|
static int |
SELECTION_GREEDY
Attribute selection method: Greedy method |
static int |
SELECTION_M5
Attribute selection method: M5 method |
static int |
SELECTION_NONE
Attribute selection method: No attribute selection |
static Tag[] |
TAGS_SELECTION
Attribute selection methods |
Constructor Summary | |
---|---|
LinearRegression()
|
Method Summary | |
---|---|
java.lang.String |
attributeSelectionMethodTipText()
Returns the tip text for this property |
void |
buildClassifier(Instances data)
Builds a regression model for the given data. |
double |
classifyInstance(Instance instance)
Classifies the given instance using the linear regression function. |
double[] |
coefficients()
Returns the coefficients for this linear model. |
java.lang.String |
debugTipText()
Returns the tip text for this property |
java.lang.String |
eliminateColinearAttributesTipText()
Returns the tip text for this property |
SelectedTag |
getAttributeSelectionMethod()
Gets the method used to select attributes for use in the linear regression. |
Capabilities |
getCapabilities()
Returns default capabilities of the classifier. |
boolean |
getDebug()
Controls whether debugging output will be printed |
boolean |
getEliminateColinearAttributes()
Get the value of EliminateColinearAttributes. |
java.lang.String[] |
getOptions()
Gets the current settings of the classifier. |
java.lang.String |
getRevision()
Returns the revision string. |
double |
getRidge()
Get the value of Ridge. |
java.lang.String |
globalInfo()
Returns a string describing this classifier |
java.util.Enumeration |
listOptions()
Returns an enumeration describing the available options. |
static void |
main(java.lang.String[] argv)
Generates a linear regression function predictor. |
int |
numParameters()
Get the number of coefficients used in the model |
java.lang.String |
ridgeTipText()
Returns the tip text for this property |
void |
setAttributeSelectionMethod(SelectedTag method)
Sets the method used to select attributes for use in the linear regression. |
void |
setDebug(boolean debug)
Controls whether debugging output will be printed |
void |
setEliminateColinearAttributes(boolean newEliminateColinearAttributes)
Set the value of EliminateColinearAttributes. |
void |
setOptions(java.lang.String[] options)
Parses a given list of options. |
void |
setRidge(double newRidge)
Set the value of Ridge. |
java.lang.String |
toString()
Outputs the linear regression model as a string. |
void |
turnChecksOff()
Turns off checks for missing values, etc. |
void |
turnChecksOn()
Turns on checks for missing values, etc. |
Methods inherited from class weka.classifiers.Classifier |
---|
distributionForInstance, forName, makeCopies, makeCopy |
Methods inherited from class java.lang.Object |
---|
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Field Detail |
---|
public static final int SELECTION_M5
public static final int SELECTION_NONE
public static final int SELECTION_GREEDY
public static final Tag[] TAGS_SELECTION
Constructor Detail |
---|
public LinearRegression()
Method Detail |
---|
public void turnChecksOff()
public void turnChecksOn()
public java.lang.String globalInfo()
public Capabilities getCapabilities()
getCapabilities
in interface CapabilitiesHandler
getCapabilities
in class Classifier
Capabilities
public void buildClassifier(Instances data) throws java.lang.Exception
buildClassifier
in class Classifier
data
- the training data to be used for generating the
linear regression function
java.lang.Exception
- if the classifier could not be built successfullypublic double classifyInstance(Instance instance) throws java.lang.Exception
classifyInstance
in class Classifier
instance
- the test instance
java.lang.Exception
- if classification can't be done successfullypublic java.lang.String toString()
toString
in class java.lang.Object
public java.util.Enumeration listOptions()
listOptions
in interface OptionHandler
listOptions
in class Classifier
public void setOptions(java.lang.String[] options) throws java.lang.Exception
-D Produce debugging output. (default no debugging output)
-S <number of selection method> Set the attribute selection method to use. 1 = None, 2 = Greedy. (default 0 = M5' method)
-C Do not try to eliminate colinear attributes.
-R <double> Set ridge parameter (default 1.0e-8).
setOptions
in interface OptionHandler
setOptions
in class Classifier
options
- the list of options as an array of strings
java.lang.Exception
- if an option is not supportedpublic double[] coefficients()
public java.lang.String[] getOptions()
getOptions
in interface OptionHandler
getOptions
in class Classifier
public java.lang.String ridgeTipText()
public double getRidge()
public void setRidge(double newRidge)
newRidge
- Value to assign to Ridge.public java.lang.String eliminateColinearAttributesTipText()
public boolean getEliminateColinearAttributes()
public void setEliminateColinearAttributes(boolean newEliminateColinearAttributes)
newEliminateColinearAttributes
- Value to assign to EliminateColinearAttributes.public int numParameters()
public java.lang.String attributeSelectionMethodTipText()
public void setAttributeSelectionMethod(SelectedTag method)
method
- the attribute selection method to use.public SelectedTag getAttributeSelectionMethod()
public java.lang.String debugTipText()
debugTipText
in class Classifier
public void setDebug(boolean debug)
setDebug
in class Classifier
debug
- true if debugging output should be printedpublic boolean getDebug()
getDebug
in class Classifier
public java.lang.String getRevision()
getRevision
in interface RevisionHandler
public static void main(java.lang.String[] argv)
argv
- the options
|
||||||||||
PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |