IncrementalRegressionKernel Predict

Predict responses using incremental kernel regression model

Since R2024b

• 

Libraries:
Statistics and Machine Learning Toolbox / Incremental Learning / Regression / Kernel

Description

The IncrementalRegressionKernel Predict block predicts responses for streaming data using a trained kernel regression model returned as the output of an IncrementalRegressionKernel Fit block.

Import an initial kernel regression model object into the IncrementalRegressionKernel Predict block by specifying the name of a workspace variable that contains the object. The input port mdl receives a bus signal that represents an incremental learning model fit to streaming data. The input port x receives a chunk of predictor data (observations), and the output port yfit returns predicted responses for the chunk. The optional output port CanPredict returns the prediction status of the trained model.

Examples

New

Perform Incremental Learning Using IncrementalRegressionKernel Fit and Predict Blocks

Perform incremental learning with the IncrementalRegressionKernel Fit block and predict responses with the IncrementalRegressionKernel Predict block.

• Since R2024b
• Open Live Script

Ports

Input

mdl — Incremental learning model

bus signal

Incremental learning model (incrementalRegressionKernel) fit to streaming data, specified as a bus signal (see Composite Signals (Simulink)).

x — Chunk of predictor data

numeric matrix

Chunk of predictor data, specified as a numeric matrix.

Note

The block supports only numerical input predictor data. If your input data includes categorical data, you must prepare an encoded version of the categorical data. Use dummyvar to convert each categorical variable to a numeric matrix of dummy variables. Then, concatenate all dummy variable matrices and any other numeric predictors. For more details, see Dummy Variables.

Data Types: single | double | half | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | Boolean | fixed point

Output

yfit — Chunk of predicted responses

floating-point vector

Chunk of predicted responses, returned as a floating-point vector

Note

If you specify an estimation period when you create mdl, then the predicted responses are zero during the estimation period.

Data Types: single | double

CanPredict — Model status

0 (false) | 1 (true)

Model status for prediction, returned as logical 0 (false) or 1 (true).

Note

If you specify an estimation period when you create mdl, then the model status is 0 (false) during the estimation period.

Dependencies

To enable this port, select the check box for Add output port for status of trained machine learning model on the Main tab of the Block Parameters dialog box.

Parameters

To edit block parameters interactively, use the Property Inspector. From the Simulink^® Toolstrip, on the Simulation tab, in the Prepare gallery, select Property Inspector.

Main

Select initial machine learning model — Initial incremental kernel regression model

kernelMdl (default) | incrementalRegressionKernel model object

Specify the name of a workspace variable that contains the configured incrementalRegressionKernel model object.

When you create the initial model object, the following restrictions apply:

• The predictor data cannot include categorical predictors (logical, categorical, char, string, or cell). If you supply training data in a table, the predictors must be numeric (double or single). To include categorical predictors in a model, preprocess them by using dummyvar before fitting the model.

• The NumPredictors property of the initial model must be a positive integer scalar, and must be equal to the number of predictors in x.

Programmatic Use

Block Parameter: InitialLearner

Type: character vector or string

Values: incrementalRegressionKernel object name

Default: "kernelMdl"

Add output port for status of trained machine learning model — Add second output port for model status

off (default) | on

Select the check box to include the output port CanPredict in the IncrementalRegressionKernel Predict block. This check box does not appear if the workspace already contains an incremental kernel regression model named kernelMdl, capable of prediction, when you create the IncrementalRegressionKernel Predict block. Alternatively, you can specify to include the output port CanPredict by selecting the IncrementalRegressionKernel Predict block in the Simulink workspace and entering set_param(gcb,ShowOutputCanPredict="on") at the MATLAB^® command line.

Programmatic Use

Block Parameter: ShowOutputCanPredict

Type: character vector

Values: "off" | "on"

Default: "off"

Sample time (–1 for inherited) — Option to specify sample time

–1 (default) | scalar

Specify the discrete interval between sample time hits or specify another type of sample time, such as continuous (0) or inherited (–1). For more options, see Types of Sample Time (Simulink).

By default, the IncrementalRegressionKernel Predict block inherits sample time based on the context of the block within the model.

Programmatic Use

Block Parameter: SystemSampleTime

Type: string scalar or character vector

Values: scalar

Default: "–1"

Data Types

Fixed-Point Operational Parameters

Integer rounding mode — Rounding mode for fixed-point operations

Floor (default) | Ceiling | Convergent | Nearest | Round | Simplest | Zero

Specify the rounding mode for fixed-point operations. For more information, see Rounding Modes (Fixed-Point Designer).

Block parameters always round to the nearest representable value. To control the rounding of a block parameter, enter an expression into the mask field using a MATLAB rounding function.

Programmatic Use

Block Parameter: RndMeth

Type: character vector

Values: "Ceiling" | "Convergent" | "Floor" | "Nearest" | "Round" | "Simplest" | "Zero"

Default: "Floor"

Saturate on integer overflow — Method of overflow action

off (default) | on

Specify whether overflows saturate or wrap.

Action	Rationale	Impact on Overflows	Example
Select this check box (on).	Your model has possible overflow, and you want explicit saturation protection in the generated code.	Overflows saturate to either the minimum or maximum value that the data type can represent.	The maximum value that the int8 (signed 8-bit integer) data type can represent is 127. Any block operation result greater than this maximum value causes overflow of the 8-bit integer. With the check box selected, the block output saturates at 127. Similarly, the block output saturates at a minimum output value of –128.
Clear this check box (off).	You want to optimize the efficiency of your generated code. You want to avoid overspecifying how a block handles out-of-range signals. For more information, see Troubleshoot Signal Range Errors (Simulink).	Overflows wrap to the appropriate value that the data type can represent.	The maximum value that the int8 (signed 8-bit integer) data type can represent is 127. Any block operation result greater than this maximum value causes overflow of the 8-bit integer. With the check box cleared, the software interprets the value causing the overflow as int8, which can produce an unintended result. For example, a block result of 130 (binary 1000 0010) expressed as int8 is –126.

Programmatic Use

Block Parameter: SaturateOnIntegerOverflow

Type: character vector

Values: "off" | "on"

Default: "off"

Lock output data type setting against changes by the fixed-point tools — Prevention of fixed-point tools from overriding data type

off (default) | on

Select this parameter to prevent the fixed-point tools from overriding the data type you specify for the block. For more information, see Use Lock Output Data Type Setting (Fixed-Point Designer).

Programmatic Use

Block Parameter: LockScale

Type: character vector

Values: "off" | "on"

Default: "off"

Data Type

Output data type — Data type of yfit output

Inherit: auto (default) | double | single | half | int8 | uint8 | int16 | uint16 | int32 | uint32 | int64 | uint64 | boolean | fixdt(1,16,0) | fixdt(1,16,2^0,0) | <data type expression>

Specify the data type for the yfit output. The type can be inherited, specified directly, or expressed as a data type object such as Simulink.NumericType.

When you select Inherit: auto, the block uses a rule that inherits a data type.

For more information about data types, see Control Data Types of Signals (Simulink).

Click the Show data type assistant button to display the Data Type Assistant, which helps you set the data type attributes. For more information, see Specify Data Types Using Data Type Assistant (Simulink).

Programmatic Use

Block Parameter: OutDataTypeStr

Type: character vector

Values: "Inherit: auto" | "double" | "single" | "half" | "int8" | "uint8" | "int16" | "uint16" | "int32" | "uint32" | "int64" | "uint64" | "boolean" | "fixdt(1,16,0)" | "fixdt(1,16,2^0,0)" | "<data type expression>"

Default: "Inherit: auto"

Output data type Minimum — Minimum value of yfit output for range checking

[] (default) | scalar

Specify the lower value of the yfit output range that Simulink checks.

Simulink uses the minimum value to perform:

• Parameter range checking for some blocks (see Specify Minimum and Maximum Values for Block Parameters (Simulink)).

• Simulation range checking (see Specify Signal Ranges (Simulink) and Enable Simulation Range Checking (Simulink)).

• Optimization of the code that you generate from the model. This optimization can remove algorithmic code and affect the results of some simulation modes, such as software-in-the-loop (SIL) mode or external mode. For more information, see Optimize using the specified minimum and maximum values (Embedded Coder).

Note

The Output data type Minimum parameter does not saturate or clip the actual yfit output. To do so, use the Saturation (Simulink) block instead.

Programmatic Use

Block Parameter: OutMin

Type: character vector

Values: "[]" | scalar

Default: "[]"

Output data type Maximum — Maximum value of yfit output for range checking

[] (default) | scalar

Specify the upper value of the yfit output range that Simulink checks.

Simulink uses the maximum value to perform:

• Parameter range checking for some blocks (see Specify Minimum and Maximum Values for Block Parameters (Simulink)).

• Simulation range checking (see Specify Signal Ranges (Simulink) and Enable Simulation Range Checking (Simulink)).

• Optimization of the code that you generate from the model. This optimization can remove algorithmic code and affect the results of some simulation modes, such as SIL or external mode. For more information, see Optimize using the specified minimum and maximum values (Embedded Coder).

Note

The Output data type Maximum parameter does not saturate or clip the actual yfit output. To do so, use the Saturation (Simulink) block instead.

Programmatic Use

Block Parameter: OutMax

Type: character vector

Values: "[]" | scalar

Default: "[]"

Kernel data type — Kernel computation data type

Inherit: Inherit via internal rule (default) | double | single | half | int8 | uint8 | int16 | uint16 | int32 | int64 | uint64 | uint32 | boolean | fixdt(1,16,0) | fixdt(1,16,2^0,0) | <data type expression>

Specify the data type of the parameters for Gaussian kernel approximation computation. The type can be specified directly or expressed as a data type object such as Simulink.NumericType.

When you select Inherit: Inherit via internal rule, the block uses an internal rule to determine the kernel data type. The internal rule chooses a data type that optimizes numerical accuracy, performance, and generated code size, while taking into account the properties of the embedded target hardware. The software cannot always optimize efficiency and numerical accuracy at the same time.

For more information about data types, see Control Data Types of Signals (Simulink).

Click the Show data type assistant button to display the Data Type Assistant, which helps you set the data type attributes. For more information, see Specify Data Types Using Data Type Assistant (Simulink).

Programmatic Use

Block Parameter: KernelDataTypeStr

Type: character vector

Values: 'double' | 'single' | 'half' | 'int8' | 'uint8' | 'int16' | 'uint16' | 'int32' | 'uint32' | 'uint64' | 'int64' | 'boolean' | 'fixdt(1,16,0)' | 'fixdt(1,16,2^0,0)' | '<data type expression>'

Default: 'Inherit: Inherit via internal rule'

Kernel data type Minimum — Minimum kernel computation value for range checking

[] (default) | scalar

Specify the lower value of the kernel computation internal variable range that Simulink checks.

Simulink uses the minimum value to perform:

• Parameter range checking for some blocks (see Specify Minimum and Maximum Values for Block Parameters (Simulink)).

• Simulation range checking (see Specify Signal Ranges (Simulink) and Enable Simulation Range Checking (Simulink)).

• Optimization of the code that you generate from the model. This optimization can remove algorithmic code and affect the results of some simulation modes, such as software-in-the-loop (SIL) mode or external mode. For more information, see Optimize using the specified minimum and maximum values (Embedded Coder).

Note

The Kernel data type Minimum parameter does not saturate or clip the actual kernel computation value.

Programmatic Use

Block Parameter: KernelOutMin

Type: character vector

Values: '[]' | scalar

Default: '[]'

Kernel data type Maximum — Maximum kernel computation value for range checking

[] (default) | scalar

Specify the upper value of the kernel computation internal variable range that Simulink checks.

Simulink uses the maximum value to perform:

• Parameter range checking for some blocks (see Specify Minimum and Maximum Values for Block Parameters (Simulink)).

• Simulation range checking (see Specify Signal Ranges (Simulink) and Enable Simulation Range Checking (Simulink)).

• Optimization of the code that you generate from the model. This optimization can remove algorithmic code and affect the results of some simulation modes, such as SIL or external mode. For more information, see Optimize using the specified minimum and maximum values (Embedded Coder).

Note

The Kernel data type Maximum parameter does not saturate or clip the actual kernel computation value.

Programmatic Use

Block Parameter: KernelOutMax

Type: character vector

Values: '[]' | scalar

Default: '[]'

Inner product data type — Inner product data type

double (default) | Inherit: Inherit via internal rule | single | half | int8 | uint8 | int16 | uint16 | int32 | uint32 | int64 | uint64 | boolean | fixdt(1,16,0) | fixdt(1,16,2^0,0) | <data type expression>

Specify the data type for the inner product term of the predicted response. The type can be inherited, specified directly, or expressed as a data type object such as Simulink.NumericType.

When you select Inherit: Inherit via internal rule, the block uses an internal rule to determine the inner product data type. The internal rule chooses a data type that optimizes numerical accuracy, performance, and generated code size, while taking into account the properties of the embedded target hardware. The software cannot always optimize efficiency and numerical accuracy at the same time.

For more information about data types, see Control Data Types of Signals (Simulink).

Click the Show data type assistant button to display the Data Type Assistant, which helps you set the data type attributes. For more information, see Specify Data Types Using Data Type Assistant (Simulink).

Programmatic Use

Block Parameter: InnerProductDataTypeStr

Type: character vector

Values: "Inherit: Inherit via internal rule" | "double" | "single" | "half" | "int8" | "uint8" | "int16" | "uint16" | "int32" | "uint32" | "int64" | "uint64" | "boolean" | "fixdt(1,16,0)" | "fixdt(1,16,2^0,0)" | "<data type expression>"

Default: "Inherit: Inherit via internal rule"

Inner product data type Minimum — Minimum of inner product term for range checking

[] (default) | scalar

Specify the lower value of the inner product term range that Simulink checks.

Simulink uses the minimum value to perform:

• Parameter range checking for some blocks (see Specify Minimum and Maximum Values for Block Parameters (Simulink)).

• Simulation range checking (see Specify Signal Ranges (Simulink) and Enable Simulation Range Checking (Simulink)).

• Optimization of the code that you generate from the model. This optimization can remove algorithmic code and affect the results of some simulation modes, such as software-in-the-loop (SIL) mode or external mode. For more information, see Optimize using the specified minimum and maximum values (Embedded Coder).

Note

The Inner product data type Minimum parameter does not saturate or clip the actual inner product term value.

Programmatic Use

Block Parameter: InnerProductOutMin

Type: character vector

Values: "[]" | scalar

Default: "[]"

Inner product data type Maximum — Maximum of inner product term for range checking

[] (default) | scalar

Specify the upper value of the inner product term range that Simulink checks.

Simulink uses the maximum value to perform:

• Parameter range checking for some blocks (see Specify Minimum and Maximum Values for Block Parameters (Simulink)).

• Simulation range checking (see Specify Signal Ranges (Simulink) and Enable Simulation Range Checking (Simulink)).

• Optimization of the code that you generate from the model. This optimization can remove algorithmic code and affect the results of some simulation modes, such as SIL or external mode. For more information, see Optimize using the specified minimum and maximum values (Embedded Coder).

Note

The Inner product data type Maximum parameter does not saturate or clip the actual inner product term value.

Programmatic Use

Block Parameter: InnerProductOutMax

Type: character vector

Values: "[]" | scalar

Default: "[]"

Block Characteristics

Data Types	Boolean | double | fixed point | half | integer | single
Direct Feedthrough	yes
Multidimensional Signals	no
Variable-Size Signals	no
Zero-Crossing Detection	no

Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using Simulink® Coder™.

Fixed-Point Conversion
Design and simulate fixed-point systems using Fixed-Point Designer™.

Version History

Introduced in R2024b