Open timost1234 opened 5 years ago
Why is the code for testing using l2 distance instead of cosine distance? Thank you.
embed1_train = embeddings1[train_set] embed2_train = embeddings2[train_set] _embed_train = np.concatenate((embed1_train, embed2_train), axis=0) # print(_embed_train.shape) pca_model = PCA(n_components=pca) pca_model.fit(_embed_train) embed1 = pca_model.transform(embeddings1) embed2 = pca_model.transform(embeddings2) embed1 = sklearn.preprocessing.normalize(embed1) embed2 = sklearn.preprocessing.normalize(embed2) # print(embed1.shape, embed2.shape) diff = np.subtract(embed1, embed2) dist = np.sum(np.square(diff), 1)
Hi did you got any answer to this? I was wondering the same thing
Why is the code for testing using l2 distance instead of cosine distance? Thank you.