Getting Started Guide

Contents

Batch Processing

LogitBoost classifier follows the general workflow described in Usage Model: Training and Prediction.

Training

For a description of the input and output, refer to Usage Model: Training and Prediction.
At the training stage, a LogitBoost classifier has the following parameters:
Parameter
Default Value
Description
algorithmFPType
float
The floating-point type that the algorithm uses for intermediate computations. Can be
float
or
double
.
method
defaultDense
The computation method used by the LogitBoost classifier. The only training method supported so far is the Friedman method.
weakLearnerTraining
DEPRECATED:
Pointer to an object of the stump training class.
USE INSTEAD:
Pointer to an object of the regression stump training class.
DEPRECATED:
Pointer to the training algorithm of the weak learner. By default, a stump weak learner is used.
USE INSTEAD:
Pointer to the regression training algorithm. By default, a regression stump with mse split criterion is used.
weakLearnerPrediction
DEPRECATED:
Pointer to an object of the stump prediction class.
USE INSTEAD:
Pointer to an object of the regression stump prediction class.
DEPRECATED:
Pointer to the prediction algorithm of the weak learner. By default, a stump weak learner is used.
USE INSTEAD:
Pointer to the regression prediction algorithm. By default, a regression stump with mse split criterion is used.
accuracyThreshold
0.01
LogitBoost training accuracy.
maxIterations
100
The maximal number of iterations for the LogitBoost algorithm.
nClasses
Not applicable
The number of classes, a required parameter.
weightsDegenerate
CasesThreshold
1e-10
The threshold to avoid degenerate cases when calculating weights
w
ij
.
responsesDegenerate
CasesThreshold
1e-10
The threshold to avoid degenerate cases when calculating responses
z
ij
.

Prediction

For a description of the input and output, refer to Usage Model: Training and Prediction.
At the prediction stage, a LogitBoost classifier has the following parameters:
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, the only method supported by the LogitBoost classifier at the prediction stage.
weakLearnerPrediction
DEPRECATED:
Pointer to an object of the stump prediction class.
USE INSTEAD:
Pointer to an object of the regression stump prediction class.
DEPRECATED:
Pointer to the prediction algorithm of the weak learner. By default, a stump weak learner is used.
USE INSTEAD:
Pointer to the regression prediction algorithm. By default, a regression stump with mse split criterion is used.
nClasses
Not applicable
The number of classes, a required parameter.
The algorithm terminates if it achieves the specified accuracy or reaches the specified maximal number of iterations. To determine the actual number of iterations performed, call the
getNumberOfWeakLearners()
method of the
LogitBoostModel
class and divide it by
nClasses
.

Product and Performance Information

1

Intel's compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel microprocessors. These optimizations include SSE2, SSE3, and SSSE3 instruction sets and other optimizations. Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not manufactured by Intel. Microprocessor-dependent optimizations in this product are intended for use with Intel microprocessors. Certain optimizations not specific to Intel microarchitecture are reserved for Intel microprocessors. Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice.

Notice revision #20110804