Linear Learner

orange.LinearLearner is a learner that uses the LIBLINEAR library backend that is very fast on large datasets.

LinearLearner

Linear learner learnes the attribute weights using one of the four possible methods.

Attributes

solver_type
Specifiys whitch method to use. Can be one of the folowing:
  • orange.LinearLearner.L2_LR (L2-regularized logistic regression, default)
  • orange.LinearLearner.L2LOSS_SVM_DUAL
  • orange.LinearLearner.L2LOSS_SVM
  • orange.LinearLearner.L1LOSS_SVM_DUAL
Note that only L2_LR supports probabilty esstimations.
eps
Stopping criteria (default 0.01)
C
Regularization parameter (default 1.0)

LinearClassifeir

Linear classifiers that uses one class vs. rest strategy for multi-class classification. It supports probability esstimation only if it was build with L2-regularized logistic regression learner.

Attributes

weights
A list of computed weight vectors for all one class vs. rest classifiers