quantileBinnerComponent

Pipeline component for binning data based on quantiles

Since R2026a

Description

quantileBinnerComponent is a pipeline component that bins data using quantiles as bin edges. Unless otherwise specified, the component bins data into equally-probable bins. The pipeline component uses the functionality of the quantile function during the learn phase to compute bin edges. The component uses the functionality of the discretize function during the run phase to bin new data.

Creation

Syntax

component = quantileBinnerComponent

component = quantileBinnerComponent(Name=Value)

Description

component = quantileBinnerComponent creates a pipeline component for binning data based on quantiles.

component = quantileBinnerComponent(Name=Value) sets writable Properties using one or more name-value arguments. For example, Probability=0.5 specifies to create two equally-probable bins.

Properties

Learn Parameters

The software sets learn parameters when you create the component. You can modify learn parameters using dot notation any time before you use the learn object function. Any unset learn parameters use the corresponding default values.

NumBins — Number of bins

10 (default) | positive integer scalar

Number of bins, specified as a positive integer scalar. During the learn phase, the component computes the bin edge values for NumBins equally probable bins.

Example: c = quantileBinnerComponent(NumBins=5)

Example: c.NumBins = 15

Data Types: single | double

Probability — Cumulative probabilities for which to compute bin edges

positive scalar | vector of positive scalars

Cumulative probabilities for which to compute the bin edges, specified as a positive scalar or vector of positive scalars in the range (0,1]. During the learn phase, the component computes the quantile for each cumulative probability in Probabilities, resulting in length(Probability)+1 bins.

Example: c = quantileBinnerComponent(Probability=0.3)

Example: c.Probability = [0.25 0.5 0.75]

Data Types: single | double

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

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

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

Example: c = quantileBinnerComponent(Name="Binner")

Example: c.Name = "EqualWidthBinner"

Data Types: char | string

Inputs — Names of input ports

"DataIn" (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 = quantileBinnerComponent(Inputs="Data1")

Example: c.Inputs = "X"

Data Types: char | string | cell

Outputs — Names of output ports

"DataBinned" (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 = quantileBinnerComponent(Outputs="BinnedX")

Example: c.Outputs = "X"

Data Types: char | string | cell

InputTags — Tags that enable automatic connection of component inputs

1 (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, then the number of tags must match the number of inputs in Inputs.

Example: c = quantileBinnerComponent(InputTags=2)

Example: c.InputTags = 1

Data Types: single | double

OutputTags — Tags that enable automatic connection of component outputs

1 (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, then the number of tags must match the number of outputs in Outputs.

Example: c = quantileBinnerComponent(OutputTags=0)

Example: c.OutputTags=1

Data Types: single | double

HasLearnables — Indicator for learnables

Read-only: 1 (true) (default)

This property is read-only.

Indicator for the learnables, returned as 1 (true). A value of 1 indicates that the component contains 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 and the Learnables are nonempty.

Data Types: logical

Learnables

The software sets learnables when you use the learn object function. You cannot modify learnables directly.

Edges — Bin edges

Read-only: cell array

This property is read-only.

Bin edges, returned as a vector. Since each value represents one quantile, Edges contains only the edges which divide the bins. It does not store the leading edge of the first bin or the trailing edge of the last bin.

Data Types: cell

UsedVariables — Names of variables used by component

Read-only: string array | []

This property is read-only.

Names of the variables used by the component to compute the bin edge values, returned as a string array. The variables correspond to columns in the first data argument of learn.

Data Types: string

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 Binning Data Using Quantiles

Create a quantileBinnerComponent pipeline component. Specify to bin data based on the cumulative probabilities 0.05, 0.25, 0.75, and 0.95.

component = quantileBinnerComponent(Probability=[0.05 0.25 0.75 0.95])

component = 
  quantileBinnerComponent with properties:

             Name: "QuantileBinner"
           Inputs: "DataIn"
        InputTags: 1
          Outputs: "DataBinned"
       OutputTags: 1

   
Learnables (HasLearned = false)
            Edges: []
    UsedVariables: []

   
Learn Parameters (unlocked)
          NumBins: 10
      Probability: [0.0500 0.2500 0.7500 0.9500]


Show all parameters

component is a quantileBinnerComponent object that contains two learnables: Edges and UsedVariables. These properties remains empty until you pass data to the component during the learn phase.

Load the carbig dataset. Create a table containing the Acceleration variable.

load carbig
X = table(Acceleration);

Use the learn object function to compute the bin edge values.

component = learn(component,X)

component = 
  quantileBinnerComponent with properties:

             Name: "QuantileBinner"
           Inputs: "DataIn"
        InputTags: 1
          Outputs: "DataBinned"
       OutputTags: 1

   
Learnables (HasLearned = true)
            Edges: {[4×1 double]}
    UsedVariables: "Acceleration"

   
Learn Parameters (locked)
          NumBins: 10
      Probability: [0.0500 0.2500 0.7500 0.9500]


Show all parameters

Note that the HasLearned property is set to true and the Edges and UsedVariables are nonempty.

Find the bin edge values.

edges = component.Edges{1}

edges =

   11.0000
   13.7000
   17.2000
   20.4200

Version History

Introduced in R2026a