Developer Guide

Contents

Algorithms

The Algorithms component of the
Intel® Data Analytics Acceleration Library
(
Intel® DAAL
) consists of classes that implement algorithms for data analysis (data mining), and data modeling (training and prediction). These algorithms include matrix decompositions, clustering algorithms, classification and regression algorithms, as well as association rules.
All Algorithms classes are derived from the base class
AlgorithmIface
. It provides interfaces for computations covering a variety of usage scenarios. Basic methods that you typically call are
compute()
and
finalizeCompute()
. In a very generic form algorithms accept one or several numeric tables or models as an input and return one or several numeric tables and models as an output. Algorithms may also require algorithm-specific parameters that you can modify by accessing the
parameter
field of the algorithm. Because most of algorithm parameters are preset with default values, you can often omit initialization of the parameter.

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