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By using an unsupervised training method, the HMM values can be trained without additional input from the user, such as known genome annotations.
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Kohonen SOM consists in a feed forward neural network that uses an unsupervised training (partitional clustering).
Whereas exercises in the trial by Holme et al. were supervised by physical therapists, 18 we used an unsupervised training programme.
Parameter learning in DBM is performed using an unsupervised layer-wise training procedure.
Within this context, we have developed a decision support module based on a dynamic Bayesian network that controls exercise training autonomously based on vital signs data [ 30], so that it may be used in an unsupervised training situation at home.
We shall refer to this supervised training technique as anchored training, where topics predicted using an unsupervised learning model are subsequently used as pseudo-labels to build models using a supervised learning method.
Briefly, this method is composed of three steps: (i) label the patterns from the test set (an unlabelled data block), using an unsupervised method; (ii) compute some statistics from the train and test sets, conditioned to the given class labels for train set; and (iii) compare the training and testing statistics using a multivariate hypothesis test.
In Stage 1, a set of clusters is identified using an unsupervised clustering method which is simultaneously applied to the training feature vectors extracted from the different classes.
Landsat images were processed using an unsupervised classification.
Gene expression data was clustered using an unsupervised hierarchical clustering algorithm using PermutMatrix [ 66].
Our goal in using an unsupervised method is to get an approximate grouping of data.
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