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docs/Quick Examples/estimators/cognitive/_MAD.md

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import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem'; import DocTable from "@theme/DocumentationTable";

SimpleFitMultivariateAnomaly

<Tabs defaultValue="py" values={[ {label: Python, value: py}, {label: Scala, value: scala}, ]}> <TabItem value="py">

<!--pytest-codeblocks:cont-->
python
from synapse.ml.services import *

anomalyKey = os.environ.get("ANOMALY_API_KEY", getSecret("anomaly-api-key"))
startTime = "2021-01-01T00:00:00Z"
endTime = "2021-01-03T01:59:00Z"
timestampColumn = "timestamp"
inputColumns = ["feature0", "feature1", "feature2"]
intermediateSaveDir = "wasbs://[email protected]/intermediateData"

simpleFitMultivariateAnomaly = (SimpleFitMultivariateAnomaly()
    .setSubscriptionKey(anomalyKey)
    .setLocation("westus2")
    .setOutputCol("result")
    .setStartTime(startTime)
    .setEndTime(endTime)
    .setIntermediateSaveDir(intermediateSaveDir)
    .setTimestampCol(timestampColumn)
    .setInputCols(inputColumns)
    .setSlidingWindow(50))

# uncomment below for fitting your own dataframe
# model = simpleFitMultivariateAnomaly.fit(df)
# simpleFitMultivariateAnomaly.cleanUpIntermediateData()
</TabItem> <TabItem value="scala">
scala
import com.microsoft.azure.synapse.ml.services.anomaly.FitMultivariateAnomaly

val startTime: String = "2021-01-01T00:00:00Z"
val endTime: String = "2021-01-02T12:00:00Z"
val timestampColumn: String = "timestamp"
val inputColumns: Array[String] = Array("feature0", "feature1", "feature2")
val intermediateSaveDir: String = "wasbs://[email protected]/intermediateData"
val anomalyKey = sys.env.getOrElse("ANOMALY_API_KEY", None)

val simpleFitMultivariateAnomaly = (new SimpleFitMultivariateAnomaly()
  .setSubscriptionKey(anomalyKey)
  .setLocation("westus2")
  .setOutputCol("result")
  .setStartTime(startTime)
  .setEndTime(endTime)
  .setIntermediateSaveDir(intermediateSaveDir)
  .setTimestampCol(timestampColumn)
  .setInputCols(inputColumns)
  .setSlidingWindow(50))

val df = (spark.read.format("csv")
  .option("header", True)
  .load("wasbs://[email protected]/MAD/mad_example.csv"))

val model = simpleFitMultivariateAnomaly.fit(df)

val result = (model
  .setStartTime(startTime)
  .setEndTime(endTime)
  .setOutputCol("result")
  .setTimestampCol(timestampColumn)
  .setInputCols(inputColumns)
  .transform(df))

result.show()

simpleFitMultivariateAnomaly.cleanUpIntermediateData()
model.cleanUpIntermediateData()
</TabItem> </Tabs>

<DocTable className="SimpleFitMultivariateAnomaly" py="synapse.ml.cognitive.html#module-synapse.ml.cognitive.SimpleFitMultivariateAnomaly" scala="com/microsoft/azure/synapse/ml/cognitive/SimpleFitMultivariateAnomaly.html" csharp="classSynapse_1_1ML_1_1Cognitive_1_1SimpleFitMultivariateAnomaly.html" sourceLink="https://github.com/microsoft/SynapseML/blob/master/cognitive/src/main/scala/com/microsoft/azure/synapse/ml/cognitive/MultivariateAnomalyDetection.scala" />