A data scientist trains a text sentiment classifier using SAS and wants to use pre-trained word embeddings. Which SAS capability best supports loading and using pre-trained word vectors such as Word2Vec or GloVe?
Select an answer to reveal the explanation.
Short Explanation and Infographic
Here's the deal — b is correct because SAS DLPy supports deep learning-based NLP and allows embedding layers to be initialized with pre-trained weights (e.g., Word2Vec, GloVe), which are loaded as weight tensors into the CAS deep learning engine. A is wrong because PROC TEXTMINE does not have an EMBED=YES option.
Full explanation below image
Full Explanation
B is correct because SAS DLPy supports deep learning-based NLP and allows embedding layers to be initialized with pre-trained weights (e.g., Word2Vec, GloVe), which are loaded as weight tensors into the CAS deep learning engine. A is wrong because PROC TEXTMINE does not have an EMBED=YES option. C is wrong because PROC HPNEURAL does not support a PRETRAINED= option for NLP. D is wrong because PROC FACTOR performs factor/PCA analysis, not word embedding.