[mlpack-git] (blog) master: details (a778550)

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Repository : https://github.com/mlpack/blog
On branch  : master
Link       : https://github.com/mlpack/blog/compare/771ab2b5bd2db9a78d825ed83ce6a6c5090789a4...a778550a318f955adfe20465546ebf1bd4d2c894

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commit a778550a318f955adfe20465546ebf1bd4d2c894
Author: MarcosPividori <marcos.pividori at gmail.com>
Date:   Mon Jun 6 11:15:51 2016 -0300

    details


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a778550a318f955adfe20465546ebf1bd4d2c894
 content/blog/MarcosWeekTwo.md | 6 ++----
 1 file changed, 2 insertions(+), 4 deletions(-)

diff --git a/content/blog/MarcosWeekTwo.md b/content/blog/MarcosWeekTwo.md
index c2f6be8..fd0fc2f 100644
--- a/content/blog/MarcosWeekTwo.md
+++ b/content/blog/MarcosWeekTwo.md
@@ -1,5 +1,5 @@
 Title: Approximate Nearest Neighbor Search - Week 2
-Date: 2016-05-05 21:00:00
+Date: 2016-06-05 21:00:00
 Tags: gsoc, knn, kfn
 Author: Marcos Pividori
 
@@ -9,8 +9,6 @@ Then, I continued working in existing neighbor search code, updating the dual tr
 
 As we are doing approximate search, we can prune more than when an exact solution is required. For example, for knn, we consider the prune rule:
 
-```latex
-prune if $d_min(N_q, N_r) > ( 1 / (1 + \epsilon ) ) * B_1(N_q)$.
-```
+"Prune if $d_min(N_q, N_r) > ( 1 / (1 + \epsilon ) ) * B_1(N_q)$."
 
 Next week, I plan to continue working in the implementation of aprox knn, adding many test cases. Once everything is ready, I will merge it into the main repository.