reset
Description
IncCDDetector = reset( resets
        internal states of the incremental concept drift detector
        IncCDDetector)IncCDDetector, including PreviousDriftStatus and
          DriftStatus. Call reset after
          detectdrift concludes on a drift in the data.
Examples
Create a random stream such that the first 500 observations come from a normal distribution with mean 2 and standard deviation 0.75 and the next 500 come from a normal distribution with mean 4 and standard deviation 1. In an incremental drift detection application, access to data stream and model update would happen consecutively. However, for the purpose of clarification, this example demonstrates the simulation of data separately.
rng(1234) % For reproducibility numObservations = 1000; switchPeriod1 = 500; X = zeros([numObservations 1]); for i = 1:numObservations if i <= switchPeriod1 X(i) = normrnd(2,0.75); else X(i) = normrnd(4,1); end end
Initiate the incremental concept drift detector. Utilize the Hoeffding's bound method with exponential moving average method (HDDMA). Specify the input type as continuous, a warmup of 50 observations, and an estimation period of 50 observations.
incCDDetector = incrementalConceptDriftDetector("hddma",InputType="continuous", ... WarmupPeriod=50,EstimationPeriod=50)
incCDDetector = 
  HoeffdingDriftDetectionMethod
        PreviousDriftStatus: 'Stable'
                DriftStatus: 'Stable'
                     IsWarm: 0
    NumTrainingObservations: 0
                Alternative: 'greater'
                  InputType: 'continuous'
                 TestMethod: 'average'
  Properties, Methods
incDDetector is a HoeffdingDriftDetectionMethod object. When you first create the object, properties such as DriftStatus, IsWarm, CutMean, and NumTrainingObservations are at their initial state. detectdrift updates them as you feed the data incrementally and monitor for drift.
Simulate the data stream of one observation at a time and perform incremental drift detection until a drift is detected.
i=1; while incCDDetector.DriftDetected~=1 incCDDetector = detectdrift(incCDDetector,X(i)); i=i+1; if incCDDetector.DriftDetected sprintf("Drift detected at observation #%d.",i) incCDDetector end end
ans = "Drift detected at observation #518."
incCDDetector = 
  HoeffdingDriftDetectionMethod
        PreviousDriftStatus: 'Warning'
                DriftStatus: 'Drift'
                     IsWarm: 1
    NumTrainingObservations: 467
                Alternative: 'greater'
                  InputType: 'continuous'
                 TestMethod: 'average'
  Properties, Methods
The drift status switched from a Warning to a Drift (drift is detected) at observation 518. detectdrift starts updating the internal statistics after the estimation period, which is 50, hence the number of training observations is 467.
Reset and investigate the drift detector.
incCDDetector = reset(incCDDetector)
incCDDetector = 
  HoeffdingDriftDetectionMethod
        PreviousDriftStatus: 'Stable'
                DriftStatus: 'Stable'
                     IsWarm: 0
    NumTrainingObservations: 0
                Alternative: 'greater'
                  InputType: 'continuous'
                 TestMethod: 'average'
  Properties, Methods
reset function resets the internal statistics such as CutMean, PostCutMean, InputBounds, and NumTrainingObservations, the drift statuses PreviousDriftStatus and DriftStatus, and the indicators IsWarm,  DriftDetected, and WarningDetected.
Input Arguments
Incremental concept drift detector, specified as either DriftDetectionMethod or HoeffdingDriftDetectionMethod object. For more information on these
            objects and their properties, see the corresponding reference pages.
Version History
Introduced in R2022a
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