Conclusion – Introduction to Text Analytics with R Part 12

In this conclusion to Text Analytics with R we cover topics such as:

– Optimizing our model for the best generalization on new/unseen data.
– Discussion of the sensitivity/specificity trade-off of our optimized model.
– Potential next steps regarding feature engineering and algorithm selection for additional gains in effectiveness.
– For those that are interested, a collection of resources for further study to broaden and deepen their text analytics skills.

The data and R code used in this series is available here.

If you haven’t seen the rest of this series, you can check it out here.

(308)

Avatar
About The Author
- Data Science Dojo is a paradigm shift in data science learning. We enable all professionals (and students) to extract actionable insights from data.

Avatar

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <s> <strike> <strong>