# HmmTeacher - Documentation

#### What's a hidden Markov chain?

A Markov chain is an stochastic model describing a sequence of possible events in which the probability of each event depends only on the state attained in the previous event (Observed states). In a hidden Markov chain the state are not visible (hidden states), but the output of the states it is.

#### What are the observed states?

The observed states refer to the measurable and observable characteristics of the problem to be studied

#### What are the hidden states?

The hidden states are special states in which the observed states output became affected by them.

#### What are the probability matrix in a hidden Markov chain?

Each event has a probability of occurrence depending on the given condition, this are denominated emission probabilities. On the other hand there are probabilities that decide the change of events, denominated transition probabilities. Each of this probabilities are grouped making matrices with the same name.

#### What are the initial probabilities?

Las probabilidades iniciales corresponden a aquella probabilidad de que la primera observación dentro de la cadena de estados observados sea con un determinado estado oculto.

#### Backward algorithm

Explanation of the Backward algorithm. #### Forward algorithm

Explanation of the Forward algorithm. #### Viterbi algorithm

Explanation of the Viterbi algorithm. #### Example problem 1

Las probabilidades iniciales corresponden a aquella probabilidad de que la primera observación dentro de la cadena de estados observados sea con un determinado estado oculto.

#### Example problem 2

Las probabilidades iniciales corresponden a aquella probabilidad de que la primera observación dentro de la cadena de estados observados sea con un determinado estado oculto.