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;
-}