Developer Guide for Intel® Data Analytics Acceleration Library 2019 Update 1
Given n feature vectors x1=(x11,…,x1p),..., xn=(xn1,…,xnp) of size p, the number of classes K, and a vector of class labels y=(y1,…,yn), where yi ∈ {0, 1 ,... ,K-1}, the problem is to build a multi-class classifier using a two-class (binary) classifier, such as a two-class SVM.
The model is trained with the One-Against-One method that uses the binary classification described in [Hsu02] as follows (for more references, see the Bibliography in [Hsu02]): For each pair of classes (i, j), train a binary classifier, such as SVM. The total number of such binary classifiers is K(K-1)/2.
Given a new feature vector xi, the classifier determines the class to which the vector belongs.
Intel DAAL provides two methods for class label prediction: