Merging upstream version 1.39.0.

Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>

1 files changed, 0 insertions, 43 deletions

diff --git a/ml/KMeans.cc b/ml/KMeans.cc
deleted file mode 100644
index edc2ef49e..000000000
--- a/ml/KMeans.cc
+++ /dev/null
@@ -1,43 +0,0 @@
-// SPDX-License-Identifier: GPL-3.0-or-later
-
-#include "KMeans.h"
-#include <dlib/clustering.h>
-
-void KMeans::train(const std::vector<DSample> &Samples, size_t MaxIterations) {
-    MinDist = std::numeric_limits<CalculatedNumber>::max();
-    MaxDist = std::numeric_limits<CalculatedNumber>::min();
-
-    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(const DSample &Sample) const {
-    CalculatedNumber MeanDist = 0.0;
-    for (const auto &CC: ClusterCenters)
-        MeanDist += dlib::length(CC - Sample);
-
-    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;
-}