Mean Squared Error Algorithm
Mean Squared Error Algorithm is not supported on GPU.
Details
Given
, a set of feature vectors
,
and a set of respective responses
,
the mean squared error (MSE) objective function
is a function that has the format:
In oneDAL implementation of the MSE, the
is represented as:
For a given set of the indices
,
,
,
,
the value and the gradient of the sum of functions in the argument
respectively have the format:
where
Computation
Algorithm Input
The mean squared error algorithm accepts the input described below.
Pass the
Input ID
as a parameter to the methods that provide input for your algorithm.
For more details, see Algorithms.Input ID | Input |
argument | A numeric table of size |
data | A numeric table of size |
dependentVariables | A numeric table of size |
Optional Algorithm Input
The mean squared error algorithm accepts the optional input described below.
Pass the Optional
Input ID
as a parameter to the methods that provide input for your algorithm.
For more details, see Algorithms.Input ID | Input |
weights | Optional input.
Pointer to the NumericTable
except for PackedTriangularMatrix and PackedSymmetricMatrix .By default, all weights are equal to |
gramMatrix | Optional input.
Pointer to the :mathL`p times p` numeric table with pre-computed Gram matrix.
The input can be an object of any class derived from NumericTable
except for PackedTriangularMatrix and PackedSymmetricMatrix .By default, the table is set to empty numeric table. |
Algorithm Parameters
The mean squared error algorithm has the following parameters.
Some of them are required only for specific values of the computation method parameter method:
Parameter | Default value | Description |
penaltyL1 | The numeric table of size | |
penaltyL2 | The numeric table of size | |
interceptFlag | true | Flag to indicate whether or not to compute the intercept. |
algorithmFPType | float | The floating-point type that the algorithm uses for intermediate computations. Can be float or double . |
method | defaultDense | Performance-oriented computation method. |
numberOfTerms | Not applicable | The number of terms in the objective function. |
batchIndices | Not applicable | The numeric table of size This parameter can be an object of any class derived from NumericTable
except for PackedTriangularMatrix and PackedSymmetricMatrix . |
resultsToCompute | gradient | The 64-bit integer flag that specifies which characteristics of the objective function to compute. Provide one of the following values to request a single characteristic or use bitwise OR to request a combination of the characteristics:
|
Algorithm Output
For the output of the mean squared error algorithm, see Output for objective functions.
Examples
C++ (CPU)
Java*
There is no support for Java on GPU.