From the course: Machine Learning and AI Foundations: Producing Explainable AI (XAI) and Interpretable Machine Learning Solutions
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Why feature engineering is critical for IML - KNIME Tutorial
From the course: Machine Learning and AI Foundations: Producing Explainable AI (XAI) and Interpretable Machine Learning Solutions
Why feature engineering is critical for IML
- [Instructor] Feature engineering is so important that even though you'll find it discussed in more detail in other courses, I want to try to illustrate its importance with a story. Years ago, I was working with a client on a binary logistic regression model. He was exploring pediatric root canals. Until that project, I didn't know very much about them, nor did I know how common they were. He had researched them in detail. Routine dental checkups were sufficient to prevent the problem, so which children were not getting their routine checkups? It had something to do with neighborhood and location. He discovered that families that had two working adults and only one family car had trouble getting to those appointments, but this could be mitigated by access to public transportation. So why not just put location information like zip code into the model, and let the algorithm figure it out on its own? Hmm. I wish that were…
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