ecdf
Compute empirical cumulative distribution function (ecdf) for baseline and target data specified for data drift detection
Since R2022a
Description
returns the table E
= ecdf(DDiagnostics
)E
, which stores the ecdf values for all the variables
specified for drift detection in the call to the detectdrift
function.
ecdf
returns NaN
values for categorical
variables.
returns the table E
= ecdf(DDiagnostics
,Variables=variables
)E
for the variables specified by
variables
.
Examples
Compute ECDF for All Variables
Generate baseline and target data with two variables, where the distribution parameters of the second variable change for the target data.
rng('default') % For reproducibility baseline = [normrnd(0,1,100,1),wblrnd(1.1,1,100,1)]; target = [normrnd(0,1,100,1),wblrnd(1.2,2,100,1)];
Perform permutation testing for any drift between the baseline and target data.
DDiagnostics = detectdrift(baseline,target)
DDiagnostics = DriftDiagnostics VariableNames: ["x1" "x2"] CategoricalVariables: [] DriftStatus: ["Stable" "Drift"] PValues: [0.2850 0.0030] ConfidenceIntervals: [2×2 double] MultipleTestDriftStatus: "Drift" DriftThreshold: 0.0500 WarningThreshold: 0.1000 Properties, Methods
Compute the ecdf values for all variables.
E = ecdf(DDiagnostics)
E=2×3 table
x F_Baseline F_Target
______________ ______________ ______________
x1 {201×1 double} {201×1 double} {201×1 double}
x2 {201×1 double} {201×1 double} {201×1 double}
E is a table with two rows and three columns. The two rows correspond to the two variables, x1
and x2
. For each variable, ecdf
computes the ecdf values over a common domain for the baseline and target data. The function stores the common domain for each variable in the column x
, the
ecdf values for the baseline data in the column F_Baseline
, and the ecdf values for the target data in the column F_Target
.
Access the ecdf values for variable 2 in the baseline data.
E.F_Baseline{2}
ans = 201×1
0
0.0100
0.0100
0.0200
0.0300
0.0400
0.0500
0.0600
0.0700
0.0800
⋮
Plot the ecdf values of the baseline and target data for variable x2
.
stairs(E.x{2},E.F_Baseline{2},LineWidth=1.5) hold on stairs(E.x{2},E.F_Target{2},LineWidth=1.5) title('ECDF for x2') xlabel('x2') ylabel('Empirical CDF') legend('Baseline','Target',Location='east') hold off
The plot of the ecdf values also shows the drift in the distribution of the target data.
Compute ECDF Values for Specified Variables
Load the sample data.
load humanactivity
For details on the data set, enter Description
at the command line.
Assign the first 1000 observations as baseline data and the next 1000 as target data.
baseline = feat(1:1000,:); target = feat(1001:2000,:);
Test for drift on all variables.
DDiagnostics = detectdrift(baseline,target);
Compute the ecdf values for only the first five variables.
E = ecdf(DDiagnostics,Variables=[1:5])
E=5×3 table
x F_Baseline F_Target
_______________ _______________ _______________
x1 {2001×1 double} {2001×1 double} {2001×1 double}
x2 {2001×1 double} {2001×1 double} {2001×1 double}
x3 {2001×1 double} {2001×1 double} {2001×1 double}
x4 {2001×1 double} {2001×1 double} {2001×1 double}
x5 {2001×1 double} {2001×1 double} {2001×1 double}
Access the ecdf values for the third variable in the baseline data.
E.F_Baseline{3}
ans = 2001×1
0
0
0
0
0
0
0.0010
0.0020
0.0030
0.0040
⋮
Plot the ecdf values of the baseline and target data for variable x3
.
stairs(E.x{3},E.F_Baseline{3},LineWidth=1.5) hold on stairs(E.x{3},E.F_Target{3},LineWidth=1.5) title('ECDF for x3') xlabel('x3') ylabel('Empirical CDF') legend('Baseline','Target',Location = 'southeast') hold off
The ecdf plot shows the drift in the target data for variable x3
.
Input Arguments
DDiagnostics
— Diagnostics of permutation testing for drift detection
DriftDiagnostics
object
Diagnostics of the permutation testing for drift detection, specified as a DriftDiagnostics
object returned by detectdrift
.
variables
— List of variables
string array | cell array of character vectors | integer indices
List of variables for which to compute the ecdf values, specified as a string array, cell array of character vectors, or list of integer indices.
Example: Variables=["x1","x3"]
Example: Variables=(1,3)
Data Types: single
| double
| char
| string
Output Arguments
E
— ecdf values
table
ecdf values for all variables specified for drift detection in the call to
detectdrift
, returned as a table with the following columns.
Column Name | Description |
---|---|
x | Common domain over which to evaluate the empirical cdf |
F_Baseline | ecdf values for the baseline data |
F_Target | ecdf values for the target data |
For each variable in E
, the columns store x
and the ecdf values in cell arrays. To access the values, you can index into the table;
for example, to obtain the ecdf values for the second variable in the baseline data, use
E.F_Baseline{2,1}
.
Version History
Introduced in R2022a
See Also
detectdrift
| DriftDiagnostics
| plotDriftStatus
| plotEmpiricalCDF
| plotHistogram
| plotPermutationResults
| summary
| histcounts
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