From 1418c7b5f1604fdd80bf235cdbc17e1a702d7fba Mon Sep 17 00:00:00 2001
From: Ron Weiss <ronweiss@gmail.com>
Date: Sun, 7 Nov 2010 16:15:55 -0500
Subject: [PATCH] add HMM.predict_proba
---
scikits/learn/hmm.py | 19 +++++++++++++++++++
1 file changed, 19 insertions(+)
diff --git a/scikits/learn/hmm.py b/scikits/learn/hmm.py
index 1fffddcda5..1191e5932d 100644
--- a/scikits/learn/hmm.py
+++ b/scikits/learn/hmm.py
@@ -231,6 +231,25 @@ class _BaseHMM(BaseEstimator):
logprob, state_sequence = self.decode(obs, **kwargs)
return state_sequence
+ def predict_proba(self, obs, **kwargs):
+ """Compute the posterior probability for each state in the model
+
+ Parameters
+ ----------
+ obs : array_like, shape (n, n_dim)
+ List of n_dim-dimensional data points. Each row corresponds to a
+ single data point.
+
+ See eval() for a list of accepted keyword arguments.
+
+ Returns
+ -------
+ T : array-like, shape (n, n_states)
+ Returns the probability of the sample for each state in the model.
+ """
+ logprob, posteriors = self.eval(obs, **kwargs)
+ return posteriors
+
def rvs(self, n=1):
"""Generate random samples from the model.
--
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