What step converts the processed text into numerical vectors for model analysis?

What step converts the processed text into numerical vectors for model analysis?

• A. Feature Extraction
• B. Bag of Words
• C. Term Frequency (TF)
• D. Dictionary (Heuristic)

Answer: (A)

Converting processed text into numerical vectors for model analysis is a feature extraction step. After cleaning and tokenizing text, you need to derive numeric features that a model can process. Feature extraction is the broad process of turning text into numbers, capturing information like word presence or frequency, and it encompasses popular methods such as Bag of Words or term frequency, TF-IDF, and more advanced embeddings. Bag of Words is one way to implement this: you build a vocabulary from the corpus and represent each document as a vector of counts (or binary indicators) for those words. Term Frequency is a specific metric within this space that measures how often each term appears in a document. Dictionary (Heuristic) isn’t a standard, general step for creating numerical vectors; it refers more to predefined mappings or rules rather than the transformation process itself.

Converting processed text into numerical vectors for model analysis is a feature extraction step. After cleaning and tokenizing text, you need to derive numeric features that a model can process. Feature extraction is the broad process of turning text into numbers, capturing information like word presence or frequency, and it encompasses popular methods such as Bag of Words or term frequency, TF-IDF, and more advanced embeddings.

Bag of Words is one way to implement this: you build a vocabulary from the corpus and represent each document as a vector of counts (or binary indicators) for those words. Term Frequency is a specific metric within this space that measures how often each term appears in a document. Dictionary (Heuristic) isn’t a standard, general step for creating numerical vectors; it refers more to predefined mappings or rules rather than the transformation process itself.