An earlier column ordering error has been corrected, emphasizing the importance of accurate column placement for data modeling. Clarifying the correct position of "age" ensures proper predictions and model accuracy.
Key Insights
- Corrected an earlier error by repositioning the "age" column from second to fourth, highlighting the critical importance of column order in model analysis.
- Emphasized that the model does not inherently identify column names or their meanings but rather depends entirely on column positions for predictions.
- Recommended rerunning all previous code after correcting column order to ensure data consistency and accuracy before proceeding.
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Quick note on an error I made in the earlier version of this. I had 'Age' second here instead of, I think, fourth. And that matters because the model doesn't know what any of these columns represent.
It doesn't know what their names are or what they represent. So, the order is all that it knows. It knows that column four appeared to be a pretty good predictor, and that was Age.
So, here I've restored it to the original version that I'm about to correct. You should move 'Age' to fourth if you're following along with the earlier video. Then, to make sure we're keeping this all straight, I'm going to run all the previous code.
We'll start off in the correct place. And then I'm going to run this. Great.
Now I'm going to run the next line, which I was starting to run before.