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.
Kaggle Spam Data Set
The data and R code here
Introduction to Text Analytics with R
More Data Science Material:
[Video Series] Beginning R Programming
[Video Series] Creating a Kaggle Model using R
[Blog] Natural Language Processing with R Programming Books