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Module: Trainer Bio/HMM/Trainer.py

Provide trainers which estimate parameters based on training sequences.

These should be used to train a Markov Model prior to actually using it to decode state paths. When supplied training sequences and a model to work from, these classes will estimate paramters of the model.

This aims to estimate two parameters:

  • a_{kl} -- the number of times there is a transition from k to l in the training data.

  • e_{k}(b) -- the number of emissions of the state b from the letter k in the training data.

Imported modules   
from DynamicProgramming import ScaledDPAlgorithms
import math
Classes   
AbstractTrainer

Provide generic functionality needed in all trainers.

BaumWelchTrainer

Trainer that uses the Baum-Welch algorithm to estimate parameters.

KnownStateTrainer

Estimate probabilities with known state sequences.

TrainingSequence

Hold a training sequence with emissions and optionally, a state path.


Table of Contents

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