summaryrefslogtreecommitdiffstats
path: root/ml/Config.cc
diff options
context:
space:
mode:
authorDaniel Baumann <daniel.baumann@progress-linux.org>2022-04-14 18:12:10 +0000
committerDaniel Baumann <daniel.baumann@progress-linux.org>2022-04-14 18:12:10 +0000
commitb5321aff06d6ea8d730d62aec2ffd8e9271c1ffc (patch)
tree36c41e35994786456154f9d3bf88c324763aeea4 /ml/Config.cc
parentAdding upstream version 1.33.1. (diff)
downloadnetdata-b5321aff06d6ea8d730d62aec2ffd8e9271c1ffc.tar.xz
netdata-b5321aff06d6ea8d730d62aec2ffd8e9271c1ffc.zip
Adding upstream version 1.34.0.upstream/1.34.0
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
Diffstat (limited to 'ml/Config.cc')
-rw-r--r--ml/Config.cc20
1 files changed, 15 insertions, 5 deletions
diff --git a/ml/Config.cc b/ml/Config.cc
index df0a2825e..99109e05f 100644
--- a/ml/Config.cc
+++ b/ml/Config.cc
@@ -32,10 +32,13 @@ void Config::readMLConfig(void) {
unsigned MinTrainSamples = config_get_number(ConfigSectionML, "minimum num samples to train", 1 * 3600);
unsigned TrainEvery = config_get_number(ConfigSectionML, "train every", 1 * 3600);
+ unsigned DBEngineAnomalyRateEvery = config_get_number(ConfigSectionML, "dbengine anomaly rate every", 60);
+
unsigned DiffN = config_get_number(ConfigSectionML, "num samples to diff", 1);
unsigned SmoothN = config_get_number(ConfigSectionML, "num samples to smooth", 3);
unsigned LagN = config_get_number(ConfigSectionML, "num samples to lag", 5);
+ double RandomSamplingRatio = config_get_float(ConfigSectionML, "random sampling ratio", 1.0 / LagN);
unsigned MaxKMeansIters = config_get_number(ConfigSectionML, "maximum number of k-means iterations", 1000);
double DimensionAnomalyScoreThreshold = config_get_float(ConfigSectionML, "dimension anomaly score threshold", 0.99);
@@ -59,10 +62,13 @@ void Config::readMLConfig(void) {
MinTrainSamples = clamp(MinTrainSamples, 1 * 3600u, 6 * 3600u);
TrainEvery = clamp(TrainEvery, 1 * 3600u, 6 * 3600u);
+ DBEngineAnomalyRateEvery = clamp(DBEngineAnomalyRateEvery, 1 * 30u, 15 * 60u);
+
DiffN = clamp(DiffN, 0u, 1u);
SmoothN = clamp(SmoothN, 0u, 5u);
- LagN = clamp(LagN, 0u, 5u);
+ LagN = clamp(LagN, 1u, 5u);
+ RandomSamplingRatio = clamp(RandomSamplingRatio, 0.2, 1.0);
MaxKMeansIters = clamp(MaxKMeansIters, 500u, 1000u);
DimensionAnomalyScoreThreshold = clamp(DimensionAnomalyScoreThreshold, 0.01, 5.00);
@@ -102,10 +108,13 @@ void Config::readMLConfig(void) {
Cfg.MinTrainSamples = MinTrainSamples;
Cfg.TrainEvery = TrainEvery;
+ Cfg.DBEngineAnomalyRateEvery = DBEngineAnomalyRateEvery;
+
Cfg.DiffN = DiffN;
Cfg.SmoothN = SmoothN;
Cfg.LagN = LagN;
+ Cfg.RandomSamplingRatio = RandomSamplingRatio;
Cfg.MaxKMeansIters = MaxKMeansIters;
Cfg.DimensionAnomalyScoreThreshold = DimensionAnomalyScoreThreshold;
@@ -120,9 +129,10 @@ void Config::readMLConfig(void) {
Cfg.HostsToSkip = config_get(ConfigSectionML, "hosts to skip from training", "!*");
Cfg.SP_HostsToSkip = simple_pattern_create(Cfg.HostsToSkip.c_str(), NULL, SIMPLE_PATTERN_EXACT);
- Cfg.ChartsToSkip = config_get(ConfigSectionML, "charts to skip from training",
- "!system.* !cpu.* !mem.* !disk.* !disk_* "
- "!ip.* !ipv4.* !ipv6.* !net.* !net_* !netfilter.* "
- "!services.* !apps.* !groups.* !user.* !ebpf.* !netdata.* *");
+ // Always exclude anomaly_detection charts from training.
+ Cfg.ChartsToSkip = "anomaly_detection.* ";
+ Cfg.ChartsToSkip += config_get(ConfigSectionML, "charts to skip from training", "netdata.*");
Cfg.SP_ChartsToSkip = simple_pattern_create(ChartsToSkip.c_str(), NULL, SIMPLE_PATTERN_EXACT);
+
+ Cfg.StreamADCharts = config_get_boolean(ConfigSectionML, "stream anomaly detection charts", true);
}