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
Reset Drift Detector After Detection of Drift
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'
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'
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'
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
IncCDDetector
— Incremental concept drift detector
DriftDetectionMethod
| HoeffdingDriftDetectionMethod
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
MATLAB 명령
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