Hands-On Machine Learning with C++

Factor analysis

In the Shogun library, the factor analysis algorithm is implemented in the CFactorAnalysis class. Objects of this class should be configured with the target number of dimensions. The set_target_dim() method should be used to modify the value of the target dimensions, while the fit() and transform() methods should be used for training and data dimensionality reduction, respectively:

 void FAReduction(Some<CDenseFeatures<DataType>> features,                  const int target_dim) {   auto fa = some<CFactorAnalysis>();   fa->set_target_dim(target_dim);   fa->fit(features);    auto new_features =       static_cast<CDenseFeatures<DataType> *>(fa->transform(features));    auto feature_matrix = new_features->get_feature_matrix(); for (index_t i = 0; i < new_features->get_num_vectors(); ...