From 57392821f3b7e0909578da0ff95c8aae4322bb4d Mon Sep 17 00:00:00 2001
From: osdf <osendorf@gmail.com>
Date: Tue, 14 Dec 2010 17:44:10 +0100
Subject: [PATCH] Fixed problem with big full covariance matrices: sum,log
instead of log,prod for loglikelihood computations.
---
scikits/learn/mixture.py | 4 ++--
1 file changed, 2 insertions(+), 2 deletions(-)
diff --git a/scikits/learn/mixture.py b/scikits/learn/mixture.py
index 47247c3c69..7b9a5bf733 100644
--- a/scikits/learn/mixture.py
+++ b/scikits/learn/mixture.py
@@ -561,10 +561,10 @@ def _lmvnpdffull(obs, means, covars):
log_prob = np.empty((nobs,nmix))
for c, (mu, cv) in enumerate(itertools.izip(means, covars)):
cv_chol = linalg.cholesky(cv, lower=True)
- cv_det = np.prod(np.diagonal(cv_chol))**2
+ cv_log_det = 2*np.sum(np.log(np.diagonal(cv_chol)))
cv_sol = solve_triangular(cv_chol, (obs - mu).T, lower=True).T
log_prob[:, c] = -.5 * (np.sum(cv_sol**2, axis=1) + \
- ndim * np.log(2 * np.pi) + np.log(cv_det))
+ ndim * np.log(2 * np.pi) + cv_log_det))
return log_prob
--
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