Logistic Regression Learner

Logistic Regression Learner

Signals

Inputs:

• Data

  A table with training instances

Outputs:

• Learner

  The logistic regression learning algorithm with settings as specified in the dialog.

• Logistic Regression Classifier

  Trained classifier (a subtype of Classifier)

Signal Logistic Regression Classifier sends data only if the learning data (signal Data) is present.

Description

This widget provides a graphical interface to the logistic regression classifier.

As all widgets for classification, this widget provides a learner and classifier on the output. Learner is a learning algorithm with settings as specified by the user. It can be fed into widgets for testing learners, for instance Test Learners. Classifier is a logistic regression classifier (a subtype of a general classifier), built from the training examples on the input. If examples are not given, there is no classifier on the output.

1. Learner can be given a name under which it will appear in, say, Test Learners. The default name is “Logistic regression”.
2. Set the regularization type (L1 or L2 weight penalty).
3. Set error cost paramter (higher cost means less regularization).
4. Normalize the features before training.

Examples

The widget is used just as any other widget for inducing classifier. See, for instance, the example for the Naive Bayesian Learner.