observationRemoverComponent

Pipeline component for removing observations

Since R2026a

Description

observationRemoverComponent is a pipeline component that removes observations in the data. During the learn and run phases, the pipeline component can remove observations based on a removal function. By default, the component does not remove observations during the run phase. For more information, see RunRemoval.

Creation

Syntax

component = observationRemoverComponent

component = observationRemoverComponent(Name=Value)

Description

component = observationRemoverComponent creates a pipeline component for removing observations.

component = observationRemoverComponent(Name=Value) sets writable Properties using one or more name-value arguments. For example, you can specify the removal criteria function using the FunctionHandle name-value argument.

Properties

Structural Parameters

The software sets structural parameters when you create the component. You cannot modify structural parameters after the component is created.

FunctionHandle — Function handle to specify removal criteria

@ismissing (default) | function handle

This property is read-only after the component is created.

Function handle to specify removal criteria, specified as a function handle. The component applies FunctionHandle to the data argument specified by ReferenceInput and removes any observations that produce a nonzero value.

FunctionHandle must follow the signature Y = myfun(X), where X is a table and Y is a table or array with the same number of rows as X.

Example: c = observationRemoverComponent(FunctionHandle=@myfun)

Example: c.FunctionHandle = @ismissing

Data Types: function_handle

NumDataFlow — Number of data flow tags to include in component

2 (default) | positive integer scalar

This property is read-only after the component is created.

Number of data flow tags to include in the component, specified as a positive integer scalar. NumDataFlow determines the number of elements in InputTags and OutputTags.

Example: c = observationRemoverComponent(NumDataFlow=1)

Data Types: single | double

ReferenceInput — Index of data argument used to identify observations to remove

1 (default) | positive integer scalar

This property is read-only after the component is created.

Index of the data argument passed to learn or run that is used to detect observations to remove, specified as a positive integer scalar. The component identifies observations for removal by applying FunctionHandle to the ReferenceInput data argument of learn or run.

While the component uses only the data specified by ReferenceInput to identify observations to remove, the identified observations are removed from all the data arguments passed to learn or run.

Example: c = observationRemoverComponent(ReferenceInput=2)

Data Types: single | double

Run Parameters

The software sets run parameters when you create the component. You can modify the run parameters at any time. Any unset run parameters use the corresponding default values.

RunRemoval — Flag for removing observations during run phase

false or 0 (default) | true or 1

Flag for removing observations during the run phase, specified as 0 (false) or 1 (true). If RunRemoval is true, the software removes observations from the data arguments passed to run. If RunRemoval is false, the software does not remove any observations from the data arguments passed to run and outputs the unchanged data.

Example: c = observationRemoverComponent(RunRemoval=true)

Example: c.RunRemoval = false

Data Types: logical

Component Properties

The software sets component properties when you create the component. You can modify the component properties (excluding HasLearnables and HasLearned) using dot notation at any time. You cannot modify the HasLearnables and HasLearned properties directly.

Name — Component identifier

"ObservationRemover" (default) | character vector | string scalar

Component identifier, specified as a character vector or string scalar.

Example: c = observationRemoverComponent(Name="RemoveObservations")

Example: c.Name = "RemoveMissing"

Data Types: char | string

Inputs — Names of input ports

["DataIn1" "DataIn2"] (default) | character vector | string array | cell array of character vectors

Names of the input ports, specified as a character vector, string array, or cell array of character vectors.

Example: c = observationRemoverComponent(Inputs=["Data1","Data2"])

Example: c.Inputs = ["X","Y"]

Data Types: char | string | cell

Outputs — Names of output ports

["DataOut1","DataOut2"] (default) | character vector | string array | cell array of character vectors

Names of the output ports, specified as a character vector, string array, or cell array of character vectors.

Example: c = observationRemoverComponent(Outputs=["Data1","Data2"])

Example: c.Outputs = ["X","Y"]

Data Types: char | string | cell

InputTags — Tags that enable automatic connection of component inputs

[1 2] (default) | nonnegative integer vector

Tags that enable the automatic connection of the component inputs with other components or pipelines, specified as a nonnegative integer vector. If you specify InputTags, the number of tags must match the number of inputs in Inputs.

Example: c = observationRemoverComponent(InputTags=[1 2])

Example: c.InputTags = [2 1]

Data Types: single | double

OutputTags — Tags that enable automatic connection of component outputs

[1 2] (default) | nonnegative integer vector

Tags that enable the automatic connection of the component outputs with other components or pipelines, specified as a nonnegative integer vector. If you specify OutputTags, the number of tags must match the number of outputs in Outputs.

Example: c = observationRemoverComponent(OutputTags=[1 0])

Example: c.OutputTags=[1 2]

Data Types: single | double

HasLearnables — Indicator for learnables

Read-only: 0 (false) (default)

This property is read-only.

Indicator for the learnables, returned as 0 (false). A value of 0 indicates that the component does not contain learnables.

Data Types: logical

HasLearned — Indicator showing learning status of component

Read-only: 0 (false) (default) | 1 (true)

This property is read-only.

Indicator showing the learning status of the component, returned as 0 (false) or 1 (true). A value of 1 indicates that the learn object function has been applied to the component..

Data Types: logical

Object Functions

learn	Initialize and evaluate pipeline or component
run	Execute pipeline or component for inference after learning
reset	Reset pipeline or component
series	Connect components in series to create pipeline
parallel	Connect components or pipelines in parallel to create pipeline
view	View diagram of pipeline inputs, outputs, components, and connections

Examples

Create Pipeline Component for Removing Observations with Missing Values

Create a, observationRemoverComponent pipeline component. Specify to remove observations based on the second data argument. The component will remove any observations that have a missing value in the response variable.

component = observationRemoverComponent(ReferenceInput=2)

component = 
  observationRemoverComponent with properties:

              Name: "ObservationRemover"
            Inputs: ["DataIn1"    "DataIn2"]
         InputTags: [1 2]
           Outputs: ["DataOut1"    "DataOut2"]
        OutputTags: [1 2]

   
Learnables (HasLearned = false)
    No properties.

   
Structural Parameters (locked)
       NumDataFlow: 2
    ReferenceInput: 2
    FunctionHandle: @ismissing

   
Run Parameters (unlocked)
        RunRemoval: 0


Show all parameters

Read the carsmall data set into a table. Store the predictor and response data in the tables X and Y, respectively.

load carsmall
X = table(Cylinders,Displacement,Horsepower,Weight);
Y = table(MPG);

Use the learn object function to learn the component and remove observations with missing response values from the data.

[component,newX,newY] = learn(component,X,Y);
component

component = 
  observationRemoverComponent with properties:

              Name: "ObservationRemover"
            Inputs: ["DataIn1"    "DataIn2"]
         InputTags: [1 2]
           Outputs: ["DataOut1"    "DataOut2"]
        OutputTags: [1 2]

   
Learnables (HasLearned = true)
    No properties.

   
Structural Parameters (locked)
       NumDataFlow: 2
    ReferenceInput: 2
    FunctionHandle: @ismissing

   
Run Parameters (unlocked)
        RunRemoval: 0


Show all parameters

Note that the HasLearned property is set to true, indicating that the component has learned.

Compute the number of missing observations removed by the component.

missing = height(X)-height(newX)

missing = 6

Version History

Introduced in R2026a