python - how PCA fit transform on test set -
i using from sklearn.decomposition import pca library, incrementalpca reduce dimensionality of problem follows:
training_data = [...] training_target = [...] test_data = [...] test_target = [...] ipca = incrementalpca(n_components, batch_size) new_training_data = ipca.fit_transform(training_data) to run tests given classifier, need fit test set information obtained in training set (something eigenvalues , eigenvectors), reduce same size of new training set. how can this library (or other), since ipca.fit_transform(data) not return me eg eigpairs or value resize dimension of test set?
the transform internal incrementalpca object after call fit or fit_transform. when call icpa.fit_transform, telling determine principal components transform given data , apply transform data. transform data set, use transform method of trained incrementalpca object:
new_test_data = icpa.transform(test_data)
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