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.

For more complete information about compiler optimizations, see our Optimization Notice.
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