Developer Guide


Data Model

The Data Model component of the
Intel® Data Analytics Acceleration Library
Intel® DAAL
) provides classes for model representation. The model mimics the actual data and represents it in a compact way so that you can use the library when the actual data is missing, incomplete, noisy or unavailable.
There are two categories of models in the library: Regression models and Classification models. Regression models are used to predict the values of dependent variables (responses) by observing independent variables. Classification models are used to predict to which sub-population (class) a given observation belongs.
A set of parameters characterizes each model.
Intel DAAL
model classes provide interfaces to access these parameters. It also provides the corresponding classes to train models, that is, to estimate model parameters using training data sets. As soon as a model is trained, it can be used for prediction and cross-validation. For this purpose, the library provides the corresponding prediction classes.

Product and Performance Information


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