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authorDaniel Baumann <daniel.baumann@progress-linux.org>2022-11-30 18:47:05 +0000
committerDaniel Baumann <daniel.baumann@progress-linux.org>2022-11-30 18:47:05 +0000
commit97e01009d69b8fbebfebf68f51e3d126d0ed43fc (patch)
tree02e8b836c3a9d89806f3e67d4a5fe9f52dbb0061 /ml/kmeans/KMeans.cc
parentReleasing debian version 1.36.1-1. (diff)
downloadnetdata-97e01009d69b8fbebfebf68f51e3d126d0ed43fc.tar.xz
netdata-97e01009d69b8fbebfebf68f51e3d126d0ed43fc.zip
Merging upstream version 1.37.0.
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
Diffstat (limited to 'ml/kmeans/KMeans.cc')
-rw-r--r--ml/kmeans/KMeans.cc55
1 files changed, 0 insertions, 55 deletions
diff --git a/ml/kmeans/KMeans.cc b/ml/kmeans/KMeans.cc
deleted file mode 100644
index e66c66c16..000000000
--- a/ml/kmeans/KMeans.cc
+++ /dev/null
@@ -1,55 +0,0 @@
-// SPDX-License-Identifier: GPL-3.0-or-later
-
-#include "KMeans.h"
-#include <dlib/clustering.h>
-
-void KMeans::train(SamplesBuffer &SB, size_t MaxIterations) {
- std::vector<DSample> Samples = SB.preprocess();
-
- MinDist = std::numeric_limits<CalculatedNumber>::max();
- MaxDist = std::numeric_limits<CalculatedNumber>::min();
-
- {
- std::lock_guard<std::mutex> Lock(Mutex);
-
- ClusterCenters.clear();
-
- dlib::pick_initial_centers(NumClusters, ClusterCenters, Samples);
- dlib::find_clusters_using_kmeans(Samples, ClusterCenters, MaxIterations);
-
- for (const auto &S : Samples) {
- CalculatedNumber MeanDist = 0.0;
-
- for (const auto &KMCenter : ClusterCenters)
- MeanDist += dlib::length(KMCenter - S);
-
- MeanDist /= NumClusters;
-
- if (MeanDist < MinDist)
- MinDist = MeanDist;
-
- if (MeanDist > MaxDist)
- MaxDist = MeanDist;
- }
- }
-}
-
-CalculatedNumber KMeans::anomalyScore(SamplesBuffer &SB) {
- std::vector<DSample> DSamples = SB.preprocess();
-
- std::unique_lock<std::mutex> Lock(Mutex, std::defer_lock);
- if (!Lock.try_lock())
- return std::numeric_limits<CalculatedNumber>::quiet_NaN();
-
- CalculatedNumber MeanDist = 0.0;
- for (const auto &CC: ClusterCenters)
- MeanDist += dlib::length(CC - DSamples.back());
-
- MeanDist /= NumClusters;
-
- if (MaxDist == MinDist)
- return 0.0;
-
- CalculatedNumber AnomalyScore = 100.0 * std::abs((MeanDist - MinDist) / (MaxDist - MinDist));
- return (AnomalyScore > 100.0) ? 100.0 : AnomalyScore;
-}