diff options
Diffstat (limited to 'ml/KMeans.cc')
-rw-r--r-- | ml/KMeans.cc | 43 |
1 files changed, 0 insertions, 43 deletions
diff --git a/ml/KMeans.cc b/ml/KMeans.cc deleted file mode 100644 index edc2ef49ec..0000000000 --- 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; -} |