Porto Seguro random forest starting point

Intro to Machine Learning (2018)
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I found this to be a very good starting point for using the random forest algorithm on the car insurance Kaggle. Can practice tuning the parameters from here.

https://www.kaggle.com/sidbecoolyo/random-forest-classification-0-24?scriptVersionId=1574286

1 Like
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I’m getting a 404 when I try that link.

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#fakenews

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yeah thanks I know why, hold on

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Ok please try now

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@jeremy I’m trying to apply different feature selection methods taught in the class on the insurance competition. The metric for evaluation is normalized gini index for this competition. I have few questions around the metric to use for comparing models on validation set:

  1. Can I expect that a RF classifier giving good log-loss/RMSE/accuracy is a good indicator of how well it’s gini index will be so that I can use them as proxy evaluation metric or should I directly use gini index on validation to compare models ?
  2. Are there other recommended evaluation metrics which can penalize the classifier more for false negatives ?
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All those metrics should be very correlated with gini. To penalize false negatives, try fbeta (mentioned in this week’s DL lesson for the Planet competition).

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Thanks I’ll try that