C++ API Reference for Intel® Data Analytics Acceleration Library 2019 Update 5
References | |
Analysis | |
Contains classes for analysis algorithms that are intended to uncover the underlying structure of a data set and to characterize it by a set of quantitative measures, such as statistical moments, correlations coefficients, and so on. | |
Base Classes | |
Contains 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 discovery. | |
Training and Prediction | |
Contains classes of machine learning algorithms. Unlike analysis algorithms, which are intended to characterize the structure of data sets, machine learning algorithms model the data. Modeling operates in two major stages: training and prediction or decision making. | |
Namespaces | |
daal::algorithms | |
Contains 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 discovery. | |
Classes | |
class | AnalysisContainerIface< mode > |
Abstract interface class that provides virtual methods to access and run implementations of the analysis algorithms. It is associated with the Analysis class and supports the methods for computation and finalization of the analysis results in the batch, distributed, and online modes. The methods of the container are defined in derivative containers defined for each algorithm of data analysis. More... | |
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