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RegressionGP Predict

Predict responses using Gaussian process (GP) regression model

  • Library:
  • Statistics and Machine Learning Toolbox / Regression

  • RegressionGP Predict Block Icon

Description

The RegressionGP Predict block predicts responses using a Gaussian process (GP) regression object (RegressionGP or CompactRegressionGP).

Import a trained regression object into the block by specifying the name of a workspace variable that contains the object. The input port x receives an observation (predictor data), and the output port yfit returns a predicted response for the observation. The optional outputs ysd and yint return the standard deviation and prediction intervals of the response, respectively.

Ports

Input

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Predictor data, specified as a row or column vector of one observation.

Dependencies

The variables in x must have the same order as the predictor variables that trained the model specified by Select trained machine learning model.

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

Output

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Predicted response, returned as a scalar.

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

Standard deviation of the predicted response from the predictor data, returned as a scalar.

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

Prediction intervals of the predicted response, returned as a 1-by-2 vector. yint contains the 100(1 – Alpha)% prediction interval of the predicted response yfit for the predictor data x. The Alpha value is the probability that the prediction interval does not contain the true response value for x. The first column of yint contains the lower limits of the prediction intervals, and the second column contains the upper limits.

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

Parameters

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Main

Specify the name of a workspace variable that contains a RegressionGP object or CompactRegressionGP object.

When you train the model by using fitrgp, the following restriction applies:

  • 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). Also, you cannot use the CategoricalPredictors name-value argument. To include categorical predictors in a model, preprocess the categorical predictors by using dummyvar before fitting the model.

Programmatic Use

Block Parameter: TrainedLearner
Type: workspace variable
Values: RegressionGP object | CompactRegressionGP object
Default: 'gpMdl'

Select the check box to include the optional output port ysd in the RegressionGP Predict block.

Programmatic Use

Block Parameter: ShowOutputSD
Type: character vector
Values: 'off' | 'on'
Default: 'off'

Select the check box to include the optional output port yint in the RegressionGP Predict block.

Programmatic Use

Block Parameter: ShowOutputIntervals
Type: character vector
Values: 'off' | 'on'
Default: 'off'

Specify the significance level for the confidence level of the prediction intervals yint. The confidence level of yint is equal to 100(1 – Alpha)%. For example, specify Alpha as 0.01 to return 99% prediction intervals.

Programmatic Use

Block Parameter: Alpha
Type: character vector
Values: scalar in [0 1]
Default: 0.05

Data Types

Fixed-Point Operational Parameters

Specify the rounding mode for fixed-point operations. For more information, see Rounding (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'

Specify whether overflows saturate or wrap.

ActionRationaleImpact on OverflowsExample

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 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'

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

Specify the data type of 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)' | 'fixdt(1,16,0)' | 'fixdt(1,16,2^0,0)' | '<data type expression>'
Default: 'Inherit: auto'

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

Simulink uses the minimum value to perform:

Note

The Output minimum parameter does not saturate or clip the actual yfit signal. Use the Saturation (Simulink) block instead.

Programmatic Use

Block Parameter: OutMin
Type: character vector
Values: '[]' | scalar
Default: '[]'

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

Simulink uses the maximum value to perform:

Note

The Output maximum parameter does not saturate or clip the actual yfit signal. Use the Saturation (Simulink) block instead.

Programmatic Use

Block Parameter: OutMax
Type: character vector
Values: '[]' | scalar
Default: '[]'

Specify the data type of the ysd 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: SDDataTypeStr
Type: character vector
Values: 'Inherit: auto' | 'double' | 'single' | 'half' | 'int8' | 'uint8' | 'int16' | 'uint16' | 'int32' | 'uint32' | 'int64' | 'uint64' | 'boolean' | 'fixdt(1,16)' | 'fixdt(1,16,0)' | 'fixdt(1,16,2^0,0)' | '<data type expression>'
Default: 'Inherit: auto'

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

Simulink uses the minimum value to perform:

Note

The Output standard deviation minimum parameter does not saturate or clip the actual ysd signal. Use the Saturation (Simulink) block instead.

Programmatic Use

Block Parameter: SDOutMin
Type: character vector
Values: '[]' | scalar
Default: '[]'

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

Simulink uses the maximum value to perform:

Note

The Output standard deviation maximum parameter does not saturate or clip the actual ysd signal. Use the Saturation (Simulink) block instead.

Programmatic Use

Block Parameter: SDOutMax
Type: character vector
Values: '[]' | scalar
Default: '[]'

Specify the data type of the yint 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: IntervalsDataTypeStr
Type: character vector
Values: 'Inherit: auto' | 'double' | 'single' | 'half' | 'int8' | 'uint8' | 'int16' | 'uint16' | 'int32' | 'uint32' | 'int64' | 'uint64' | 'boolean' | 'fixdt(1,16)' | 'fixdt(1,16,0)' | 'fixdt(1,16,2^0,0)' | '<data type expression>'
Default: 'Inherit: auto'

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

Simulink uses the minimum value to perform:

Note

The Output prediction intervals minimum parameter does not saturate or clip the actual yint signal. Use the Saturation (Simulink) block instead.

Programmatic Use

Block Parameter: IntervalsOutMin
Type: character vector
Values: '[]' | scalar
Default: '[]'

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

Simulink uses the maximum value to perform:

Note

The Output prediction intervals maximum parameter does not saturate or clip the actual yint signal. Use the Saturation (Simulink) block instead.

Programmatic Use

Block Parameter: IntervalsOutMax
Type: character vector
Values: '[]' | scalar
Default: '[]'

Specify the data type of the kernel function. 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).

Tips

The Kernel data type parameter specifies the data type of the kernel function in the RegressionGP model. When you use the fitrgp function to train the model, you can set the KernelFunction name-value argument to one of the values in this table.

KernelFunction ValueKernel Function Description
"exponential"Exponential kernel
"squaredexponential"Squared exponential kernel
"matern32"Matern kernel with parameter 3/2
"matern52"Matern kernel with parameter 5/2
"rationalquadratic"Rational quadratic kernel
"ardexponential"Exponential kernel with a separate length scale per predictor
"ardsquaredexponential"Squared exponential kernel with a separate length scale per predictor
"ardmatern32"Matern kernel with parameter 3/2 and a separate length scale per predictor
"ardmatern52"Matern kernel with parameter 5/2 and a separate length scale per predictor
"ardrationalquadratic"Rational quadratic kernel with a separate length scale per predictor

Programmatic Use

Block Parameter: KernelDataTypeStr
Type: character vector
Values: 'Inherit: auto' | 'double' | 'single' | 'half' | 'int8' | 'uint8' | 'int16' | 'uint16' | 'int32' | 'uint32' | 'int64' | 'uint64' | 'boolean' | 'fixdt(1,16)' | 'fixdt(1,16,0)' | 'fixdt(1,16,2^0,0)' | '<data type expression>'
Default: 'Inherit: auto'

Specify the lower value of the kernel function's internal variable range checked by Simulink.

Simulink uses the minimum value to perform:

Note

The Kernel minimum parameter does not saturate or clip the actual kernel function signal.

Programmatic Use

Block Parameter: KernelOutMin
Type: character vector
Values: '[]' | scalar
Default: '[]'

Specify the upper value of the kernel output's internal variable range checked by Simulink.

Simulink uses the maximum value to perform:

Note

The Kernel maximum parameter does not saturate or clip the actual kernel function signal.

Programmatic Use

Block Parameter: KernelOutMax
Type: character vector
Values: '[]' | scalar
Default: '[]'

Specify the data type of the method for computing kernel distance. 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 output 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).

Tips

The Distance data type parameter specifies the data type of the method for computing inter-point distances to evaluate built-in kernel functions. For more information, see the DistanceMethod name-value argument of the fitrgp function. The block always uses the value "accurate" for DistanceMethod, which does not compromise the calculation speed compared to the value "fast".

Programmatic Use

Block Parameter: DistanceDataTypeStr
Type: character vector
Values: 'Inherit: Inherit via internal rule' | 'double' | 'single' | 'half' | 'int8' | 'uint8' | 'int16' | 'uint16' | 'int32' | 'uint32' | 'int64' | 'uint64' | 'boolean' | 'fixdt(1,16)' | 'fixdt(1,16,0)' | 'fixdt(1,16,2^0,0)' | '<data type expression>'
Default: 'Inherit: Inherit via internal rule'

Specify the lower value of the kernel distance's internal variable range checked by Simulink.

Simulink uses the minimum value to perform:

Note

The Distance minimum parameter does not saturate or clip the actual kernel distance signal.

Programmatic Use

Block Parameter: DistanceOutMin
Type: character vector
Values: '[]' | scalar
Default: '[]'

Specify the upper value of the kernel distance's internal variable range checked by Simulink.

Simulink uses the maximum value to perform:

Note

The Distance maximum parameter does not saturate or clip the actual kernel distance signal.

Programmatic Use

Block Parameter: DistanceOutMax
Type: character vector
Values: '[]' | scalar
Default: '[]'

Specify the data type of the basis function. 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).

Tips

The Basis data type parameter specifies the data type of the explicit basis in the RegressionGP model. You can set the BasisFunction name-value argument when you use the fitrgp function to train the model.

Programmatic Use

Block Parameter: BasisDataTypeStr
Type: character vector
Values: 'Inherit: auto' | 'double' | 'single' | 'half' | 'int8' | 'uint8' | 'int16' | 'uint16' | 'int32' | 'uint32' | 'int64' | 'uint64' | 'boolean' | 'fixdt(1,16)' | 'fixdt(1,16,0)' | 'fixdt(1,16,2^0,0)' | '<data type expression>'
Default: 'Inherit: auto'

Specify the lower value of the basis function's internal variable range checked by Simulink.

Simulink uses the minimum value to perform:

Note

The Basis minimum parameter does not saturate or clip the actual basis function signal.

Programmatic Use

Block Parameter: BasisOutMin
Type: character vector
Values: '[]' | scalar
Default: '[]'

Specify the upper value of the basis function's internal variable range checked by Simulink.

Simulink uses the maximum value to perform:

Note

The Basis maximum parameter does not saturate or clip the actual basis function signal.

Programmatic Use

Block Parameter: BasisOutMax
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

Alternative Functionality

You can use a MATLAB Function block with the predict object function of a Gaussian process regression object (RegressionGP or CompactRegressionGP). For an example, see Predict Class Labels Using MATLAB Function Block.

When deciding whether to use the RegressionGP Predict block in the Statistics and Machine Learning Toolbox™ library or a MATLAB Function block with the predict function, consider the following:

  • If you use the Statistics and Machine Learning Toolbox library block, you can use the Fixed-Point Tool (Fixed-Point Designer) to convert a floating-point model to fixed point.

  • Support for variable-size arrays must be enabled for a MATLAB Function block with the predict function.

  • If you use a MATLAB Function block, you can use MATLAB functions for preprocessing or post-processing before or after predictions in the same MATLAB Function block.

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 R2022a