Machine Learning in Trading Strategy Design › Key Parameters
Michael BrenndoerferJanuary 3, 20261 min read
Quantitative FinanceAll chapters Part 13 of 15Machine Learning and Alternative Data
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The key parameters for the sentiment analysis pipeline are:
- ngram_range: The range of n-grams (word sequences) to extract. Including bigrams (pairs of words) captures context better than single words alone.
- max_features: The maximum number of words to include in the vocabulary. Limiting this focuses the model on the most frequent and informative terms.
- alpha: The smoothing parameter for Naive Bayes. It prevents the model from assigning zero probability to words not seen in the training data.
The next chapter provides a deeper exploration of NLP techniques and alternative data sources, including more sophisticated approaches like transformer-based models and entity extraction.