IncrementalRegressionKernel Predict
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
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
, orcell
). If you supply training data in a table, the predictors must be numeric (double
orsingle
). To include categorical predictors in a model, preprocess them by usingdummyvar
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 ParametersInteger 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
( | 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 |
Clear this check box
( | 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 |
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" |
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 |
|
Direct Feedthrough |
|
Multidimensional Signals |
|
Variable-Size Signals |
|
Zero-Crossing Detection |
|
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
See Also
Blocks
Objects
Functions
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