Create a sequence predictor function with SequencePredict and a training set of subsequences:

Use the sequence predictor function to predict the next element:

Obtain the probabilities of the next element given the sequence:

Obtain a random next element according to the preceding distribution:

Obtain multiple predictions at a time:

Predict the most likely next element and reuse this intermediate guess to predict the following element:

Predict the most likely following sequence:

Compare the probabilities for the preceding sequences:

Train a sequence predictor on a list of strings:

Predict the next character following a given string:

Predict the next four characters:

Obtain the probabilities for each character to follow the given string:

Train a sequence predictor on the list of common English words, each word treated as a sequence of characters:

Predict the most likely next character from a given sequence:

For the sequence predictor trained in the preceding example, each word is considered as a subsequence of an infinite sequence. Use the character | to mark boundaries between words:

Build a new sequence predictor aware of word boundaries:

Create an English-like word generator trimming once the boundary is found:

Load a book from ExampleData:

Train a sequence predictor on this book at character level:

Sample a random string in the book style:

Train another sequence predictor, interpreting strings as word sequences rather than character sequences:

Complete the preceding string with 10 consecutive words (spaces and punctuation marks are considered as words):

An empty list is parsed as the list with no sequences inside and will return an empty list:

To obtain the most likely next element completing an empty sequence, nest it in a second list for disambiguation: