Getting Started Guide

Contents

Classification

Classification methods split observations within a data set into a set of distinct classes by assigning class labels. Because classification is a supervised machine learning method, the training stage requires a data set that consists of both feature vectors and class labels that indicate membership of observations in a particular class. The prediction stage takes a data set (labeled or unlabeled) on input and assigns a class label to each observation.
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Product and Performance Information

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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 reservered 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