Sentence examples for sequence of labels from inspiring English sources

More formally, we are given a sequence of observations and are required to determine a sequence of labels, that is, the sequence,, with maximum posterior probability.

They take a sequence of feature vectors as inputs and generate a sequence of labels, which can be further modified during post-processing.

The rationale behind this is to consider the aggregate probability of all state paths corresponding to the same sequence of labels to improve the overall per label accuracy.

Our feature analysis shows that the most important role is played by n-grams (primarily bigrams), GRs and verbs as well as global features such as history (sequence of labels) and section headings.

Named entity recognition is typically formulated as a sequence labeling problem which can be defined as follows: given a sequence of input tokens x  = (x1 … x n ), and a set of labels L, determine a sequence of labels y  = (y1, …, y n ) for the tokens such that y i ∈ L for 1 ≤  i ≤ n.

These indicators were all evaluated using the normalized mutual information (NMI, Eq.  4) (Lancichinetti and Fortunato 2009; Danon et al. 2005), ranging from 0 to 1, with 1 indicating the same parcellation with only differences in the sequence of labels, and 0 indicating totally different parcellation.

A sequence of label commands are put into an undo buffer.

The methodology firstly characterizes the wave height time series by approximating it using a sequence of labeled segments, and then a binary classifier is trained to predict the occurrence of SSWH periods based on past height values.

Other studies with this sequence of labelling [21,104], reported high background levels of free lanthanides (mainly due to their adhesive nature), which was not discussed in this work.

Also, the three complementary techniques that were used indicate that the specific sequence of labeling intensity that we observed at the immunogold level reflects a bona fide developmental profile.

Typically X and Y are concerned with sequential data where X = (X1, X2,..., X n ) are sequences of words or sentences, and Y = (Y1, Y2,..., Y n ) are sequences of labels such as part-of-speech tags.