Visible to Intel only — GUID: GUID-295B4373-2969-42C0-A969-D4C0D02C853E
Visible to Intel only — GUID: GUID-295B4373-2969-42C0-A969-D4C0D02C853E
Logistic Loss
Logistic loss is an objective function being minimized in the process of logistic regression training when a dependent variable takes only one of two values, 0 and 1.
Details
Given n feature vectors of np-dimensional feature vectors, a vector of class labels
, where
describes the class to which the feature vector
belongs, the logistic loss objective function
has the following format
, where
is defined as
with
,
,
,
For a given set of the indices ,
,
:
The value of the sum of functions has the format:
The gradient of the sum of functions has the format:
where
For more details, see [Hastie2009].
Computation
Algorithm Input
The logistic loss 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
NOTE:
The sizes of the argument, gradient, and hessian numeric tables do not depend on interceptFlag. When interceptFlag is set to false, the computation of
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data |
A numeric table of size
NOTE:
This parameter can be an object of any class derived from NumericTable.
|
dependentVariables |
A numeric table of size
NOTE:
This parameter can be an object of any class derived from NumericTable, except for PackedTriangularMatrix , PackedSymmetricMatrix , and CSRNumericTable.
|
Algorithm Parameters
The logistic loss algorithm has the following parameters. Some of them are required only for specific values of the computation method’s parameter method:
Parameter |
Default value |
Description |
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
NOTE:
This parameter can be an object of any class derived from NumericTable except 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:
|
interceptFlag |
true |
A flag that indicates a need to compute |
penaltyL1 |
0 |
L1 regularization coefficient |
penaltyL2 |
0 |
L2 regularization coefficient |
Algorithm Output
For the output of the logistic loss algorithm, see Output for objective functions.