Characteristic engineering methods for healthcare information evaluation, specializing in real-world challenges and sensible options.
On this tutorial, we proceed the challenge Methods in Characteristic Engineering: Actual-World Healthcare Information Challenges — Half I, diving into a brand new sequence of characteristic engineering methods. Mission hyperlink: GitHub
This time, we’ll leverage area data to make characteristic engineering more practical. What does that imply? It entails understanding the precise area we’re analyzing to extract hidden insights from the dataset.
Seen info is easy — assume lacking values, outliers, creating new variables, or re-categorizing current ones. However uncovering hidden info calls for a extra in-depth method.
This stage of research typically solely turns into attainable as you acquire expertise and begin tackling superior tasks. Our focus right here is to apply characteristic engineering grounded in data particular to our area — on this case, healthcare.
