public class SequenceLearningLinearMain
extends Object
This class shows how to use a
SequenceClassificationLearningAlgorithm. Given a dataset of
SequenceExamples where each item in the sequence is represented
as a feature vector, the following code implements a very efficient
learning process operating in the feature space.
During the training step, each example is enriched to consider its history,
in terms of classes assigned to the previous example(s).
During the tagging process, the history of an example is dynamically
estimated by a classifier and the entire sequence of labels is derived
through a Viterbi Decoding step combined with a Beam Search Strategy.
The datasets used in this example have been created starting from the dataset
produced by Thorsten Joachims as an example problem for his SVM^{hmm}
implementation.
The original dataset can be downloaded at:
http://download.joachims.org/svm_hmm/examples/example7.tar.gz
while its description is reported at:
https://www.cs.cornell.edu/people/tj/svm_light/svm_hmm.html
- Author:
- Danilo Croce