Package edu.cmu.tetrad.regression

Class LogisticRegression

java.lang.Object
edu.cmu.tetrad.regression.LogisticRegression
All Implemented Interfaces:
TetradSerializable, Serializable
public class LogisticRegression extends Object implements TetradSerializable
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:

  • Constructor Details

    • LogisticRegression

      public LogisticRegression(DataSet dataSet)
      A mixed data set. The targets of regresson must be binary. Regressors must be continuous or binary. Other variables don't matter.

  • Method Details

    • serializableInstance

      public static LogisticRegression serializableInstance()
      Generates a simple exemplar of this class to test serialization.

    • regress

      public LogisticRegression.Result regress(DiscreteVariable x, List<Node> regressors)
      x must be binary; regressors must be continuous or binary.

    • getAlpha

      public double getAlpha()
      Returns:
      the alpha level.

    • setAlpha

      public void setAlpha(double alpha)
      Sets the alpha level.

    • setRows

      public void setRows(int[] rows)