Package edu.cmu.tetrad.regression
Class LogisticRegression
java.lang.Object
edu.cmu.tetrad.regression.LogisticRegression
- All Implemented Interfaces:
TetradSerializable
,Serializable
Implements a logistic regression algorithm based on a Javascript implementation by John Pezzullo. That
implementation together with a description of logistic regression and some examples appear on his web page
http://members.aol.com/johnp71/logistic.html
See also Applied Logistic Regression, by D.W. Hosmer and S. Lemeshow. 1989, John Wiley and Sons, New York which Pezzullo references. In particular see pages 27-29.
- Author:
- Frank Wimberly
- See Also:
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Nested Class Summary
Nested Classes -
Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptiondouble
getAlpha()
regress
(DiscreteVariable x, List<Node> regressors) x must be binary; regressors must be continuous or binary.static LogisticRegression
Generates a simple exemplar of this class to test serialization.void
setAlpha
(double alpha) Sets the alpha level.void
setRows
(int[] rows)
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Constructor Details
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LogisticRegression
A mixed data set. The targets of regresson must be binary. Regressors must be continuous or binary. Other variables don't matter.
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Method Details
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serializableInstance
Generates a simple exemplar of this class to test serialization. -
regress
x must be binary; regressors must be continuous or binary. -
getAlpha
public double getAlpha()- Returns:
- the alpha level.
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setAlpha
public void setAlpha(double alpha) Sets the alpha level. -
setRows
public void setRows(int[] rows)
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