MDS

A multidimensional scaling algorithm is implemented in the Shogun library in the MultidimensionalScaling class. Objects of this class should be configured, along with the number of desired features, with the set_target_dim() method. Then, the fit() method should be used for training. Unlike the previous types, this class provides the transform() method, which transforms the whole dataset into a new number of dimensions. It returns a pointer to the CDenseFeatures type object:

 void MDSReduction(Some<CDenseFeatures<DataType>> features,
                   const int target_dim) {
   auto IsoMap = some<CMultidimensionalScaling>();
   IsoMap->set_target_dim(target_dim);
   IsoMap->fit(features);
 
   auto new_features =
       static_cast<CDenseFeatures<DataType> *>(IsoMap->transform
       (features));
 
   auto feature_matrix = new_features->get_feature_matrix();
   for (index_t i = 0; i < new_features->get_num_vectors(); ++i) {
     auto new_vector = feature_matrix.get_column(i);
   }
 }

The following graph shows the result of applying the Shogun MDS algorithm to our data:

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Table of Contents for
MDS