[mlpack-git] master: Refactor to avoid issues with empty cluster action refactoring. (0495b6b)
gitdub at big.cc.gt.atl.ga.us
gitdub at big.cc.gt.atl.ga.us
Mon Jun 1 11:16:07 EDT 2015
Repository : https://github.com/mlpack/mlpack
On branch : master
Link : https://github.com/mlpack/mlpack/compare/803224f64f6b6490c3cb8aafd528b1db069ef2f1...7011dd89f6a9cf8cf7b66e1b42c9147b606551c2
>---------------------------------------------------------------
commit 0495b6bfb8a1ee21cd02fd8271d03959da4c0260
Author: Ryan Curtin <ryan at ratml.org>
Date: Mon Jun 1 11:15:26 2015 -0400
Refactor to avoid issues with empty cluster action refactoring.
>---------------------------------------------------------------
0495b6bfb8a1ee21cd02fd8271d03959da4c0260
src/mlpack/methods/kmeans/refined_start_impl.hpp | 3 ++-
1 file changed, 2 insertions(+), 1 deletion(-)
diff --git a/src/mlpack/methods/kmeans/refined_start_impl.hpp b/src/mlpack/methods/kmeans/refined_start_impl.hpp
index edceb11..4130764 100644
--- a/src/mlpack/methods/kmeans/refined_start_impl.hpp
+++ b/src/mlpack/methods/kmeans/refined_start_impl.hpp
@@ -33,7 +33,6 @@ void RefinedStart::Cluster(const MatType& data,
// We will use these objects repeatedly for clustering.
arma::Col<size_t> sampledAssignments;
arma::mat centroids;
- KMeans<> kmeans;
for (size_t i = 0; i < samplings; ++i)
{
@@ -57,6 +56,7 @@ void RefinedStart::Cluster(const MatType& data,
// cluster, we re-initialize that cluster as the point furthest away from
// the cluster with maximum variance. This is not *exactly* what the paper
// implements, but it is quite similar, and we'll call it "good enough".
+ KMeans<> kmeans;
kmeans.Cluster(sampledData, clusters, sampledAssignments, centroids);
// Store the sampled centroids.
@@ -66,6 +66,7 @@ void RefinedStart::Cluster(const MatType& data,
}
// Now, we run k-means on the sampled centroids to get our final clusters.
+ KMeans<> kmeans;
kmeans.Cluster(sampledCentroids, clusters, sampledAssignments, centroids);
// Turn the final centroids into assignments.
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