HMMDecoder Example 1: Loan Default Prediction (from Unsupervised Learner) - Teradata Vantage

Suppose you want to find the three hidden states for the table test_loan_prediction in HMMEvaluator Example: Loan Default Prediction, which is an unsupervised loan sequence trained with two models (1 and 2).

Input

• InitStateProb: pi_loan
• TransProb: A_loan
• EmissionProb: B_loan

The preceding models are output by HMMUnsupervised Example: Loan Default Prediction.

SQL Call

SELECT * FROM HMMDecoder (
  ON pi_loan AS InitStateProb PARTITION BY model_id ORDER BY model_id, state
  ON A_loan AS TransProb PARTITION BY model_id
  ON B_loan AS EmissionProb PARTITION BY model_id
  ON test_loan_prediction AS observation PARTITION BY model_id
    ORDER BY model_id, seq_id, seq_vertex_id ASC
  USING
  InitStateModelColumn ('model_id')
  InitStateColumn ('state')
  InitStateProbColumn ('probability')
  TransAttributeColumn ('model_id')
  TransFromStateColumn ('from_state')
  TransToStateColumn ('to_state')
  TransProbColumn ('probability')
  EmitModelColumn ('model_id')
  EmitStateColumn ('state')
  EmitObsColumn ('observed')
  EmitProbColumn ('probability')
  ModelColumn ('model_id')
  SeqColumn ('seq_id')
  ObsColumn ('observed_id ')
  Accumulate ('seq_vertex_id ')
) AS dt ORDER BY 1, 2, 5;

Output

For the same sequence, the hidden states are different for each model.