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IUnsupervisedLearningT Interface |
Note: This API is now obsolete.
Common interface for unsupervised learning algorithms for hidden
Markov models such as the Baum-Welch
learning and the Viterbi learning
algorithms.
Namespace: Accord.Statistics.Models.Markov.Learning
Assembly: Accord.Statistics (in Accord.Statistics.dll) Version: 3.8.0
Syntax[ObsoleteAttribute("Please use Accord.MachineLearning.IUnsupervisedLearning instead.")] public interface IUnsupervisedLearning<T> : IUnsupervisedLearning
Type Parameters
- T
Methods| Name | Description | |
|---|---|---|
 | Run(Array) |
Runs the learning algorithm.
(Inherited from IUnsupervisedLearning.) |
| Run(T) |
Runs the learning algorithm.
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RemarksIn the context of hidden Markov models, unsupervised algorithms are algorithms which consider that the sequence of states in a system is hidden, and just the system's outputs can be seen (or are known) during training. This is in contrast with supervised learning algorithms such as the Maximum Likelihood (MLE), which consider that both the sequence of observations and the sequence of states are observable during training.
See Also