7.00.02 - Input - Aster Analytics

Teradata Aster® Analytics Foundation User GuideUpdate 2

Aster Analytics
Release Number
September 2017
English (United States)
Last Update

You can use the HMMDecoder function to decode the parts of speech (adjective, noun, verb, and so on.) for a word set, if the set of phrases or words have been trained using a HMMSupervised or HMMUnsupervisedLearner. Assume that you have a set of phrases (shown in the following table) whose parts of speech are unknown and you have the three trained state tables (initial, state_transition and emission) readily available.

In this example, the parts of speech correspond to the hidden states of the HMM function. There are two hidden states in this example: A(Adjective) and N(noun). HMMDecoder can be used to find these parts of speech.

HMMDecoder Example 3 Input Table phrases
model phrase_id word
1 1 clown
1 1 crazy
1 1 killer
1 1 problem
1 2 nice
1 2 weather

The following is a table of initial states:

HMMDecoder Example 3 Input Table initial
model tag probability
1 A 0.25
1 N 0.75

The following is a table of state transitions:

HMMDecoder Example 3 Input Table state_transition
model from_tag to_tag probability
1 A A 0
1 A N 1
1 N A 0.5
1 N N 0.5

The following is a table of emissions:

HMMDecoder Example 3 Input Table emission
model tag word probability
1 A clown 0
1 N clown 0.4
1 A crazy 1
1 N crazy 0
1 A killer 0
1 N killer 0.3
1 A problem 0
1 N problem 0.3