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Bio::MarkovModel Namespace Reference


Detailed Description

This is an implementation of a state-emitting MarkovModel.  I am using
terminology similar to Manning and Schutze.



Functions:
train_bw        Train a markov model using the Baum-Welch algorithm.
train_visible   Train a visible markov model using MLE.
find_states     Find the a state sequence that explains some observations.

load            Load a MarkovModel.
save            Save a MarkovModel.

Classes:
MarkovModel     Holds the description of a markov model


Classes

class  MarkovModel

Functions

def _argmaxes
def _backward
def _baum_welch
def _baum_welch_one
def _copy_and_check
def _exp_logsum
def _forward
def _logadd
def _logsum
def _logvecadd
def _mle
def _normalize
def _random_norm
def _readline_and_check_start
def _safe_asarray
def _safe_copy_and_check
def _safe_log
def _uniform_norm
def _viterbi
def find_states
def load
def save
def train_bw
def train_visible

Variables

tuple LOG0 = log(VERY_SMALL_NUMBER)
 MATCODE = Float64
int MAX_ITERATIONS = 1000
list this_module = sys.modules[__name__]
int VERY_SMALL_NUMBER = 1


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