Feature Engineering

Once the text data is processed, it needs to be transformed into numerical features that machine learning algorithms can work with. Feature engineering involves creating features using the most relevant and informative aspects of the text data in a structured format. This step is crucial for capturing the underlying patterns and relationships within the text. Common techniques are described below.

Bag of Words (BOW)


Term Frequency–Inverse Document Frequency (TF-IDF)


Using Lexicons Models


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