Hands-On Machine Learning with C++

LDA

The LDA algorithms in the Shark-ML library are implemented in the LDA class. First, we have to train the algorithm with the train() method, which takes two parameters: the first one is a reference to the object of the LinearClassifier class, while the second is the dataset reference. Notice that the LDA algorithm uses objects of LinearClassifier because, in the Shark-ML library, LDA is used mostly for classification. Also, because this is a supervised algorithm, we should provide labels for the data. We can do this by initializing the LabeledData<RealVector, unsigned int> class object. In the following example, we can see how to combine UnlabeledData<RealVector> datasets with the labeled one. Note that labels should start from 0.

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